Bootcamp - Big Data Trunk

https://project.bigdatatrunk.com Quality Corporate and Classroom Training in Bay Area CA Thu, 01 May 2025 18:38:46 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 Byte-Sized Deep Learning Series: Demystifying Neural Networks https://project.bigdatatrunk.com/courses/byte-sized-deep-learning-series-demystifying-neural-networks/ https://project.bigdatatrunk.com/courses/byte-sized-deep-learning-series-demystifying-neural-networks/#respond Thu, 01 May 2025 18:24:13 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=58692 Step into the world of deep learning by building your first Artificial Neural Network!

The post Byte-Sized Deep Learning Series: Demystifying Neural Networks first appeared on Big Data Trunk.

]]>

Deprecated: Creation of dynamic property OMAPI_Elementor_Widget::$base is deprecated in /home2/schooli5/public_html/project/wp-content/plugins/optinmonster/OMAPI/Elementor/Widget.php on line 41

Overview
Prerequisites
Audience
Curriculum

Description:

Step into the world of deep learning by building your first Artificial Neural Network!
In this 90-minute, beginner-friendly session, you’ll uncover how neural networks learn, why activation functions are critical, and how to build a real model using TensorFlow and Keras.
If you know machine learning basics but want to start constructing real deep learning models, this is the perfect launchpad.

Duration: 90 mins

Course Code: BDT493

Learning Objectives:

After this course, you will be able to:

Demystifying Artificial Neural Networks (ANNs)
How do ANNs learn?
Building a basic ANN

Must have some python programming experience and NumPy. Students must be comfortable with TensorFlow basics

Machine learning enthusiasts and practitioners who are familiar with basic ML concepts (e.g., models, datasets, training loops). Students new to deep learning and neural networks, wanting a clear and intuitive understanding of how networks learn

Course Outline:

Demystifying Artificial Neural Networks
- What is a neural network? How does it mimic the brain?
- Core components of neural network: neurons, layers, weights, biases
- Understanding Forward and Backward pass
How do networks learn? Loss and Optimization
- The learning goal: minimizing the loss function
- Loss functions: MSE, Cross Entropy
- Optimizers: Adam, SGD
- Hands-on: Creating and Visualizing Loss
Building first neural network with Keras
- A brief introduction to Keras high-level API
- Build a simple neural network
- Compiling the model (specifying Loss and Optimizer)
- Hands-on: Build a simple neural network

Training material provided: Yes (Digital format)

Hands-on Lab: Instructions will be provided to install Jupyter notebook and other required python libraries. Students can opt to use ‘Google Colaboratory’ if they do not want to install these tools

The post Byte-Sized Deep Learning Series: Demystifying Neural Networks first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/byte-sized-deep-learning-series-demystifying-neural-networks/feed/ 0 AI and Deep Learning using Apache Spark https://project.bigdatatrunk.com/courses/ai-and-deep-learning-using-apache-spark/ https://project.bigdatatrunk.com/courses/ai-and-deep-learning-using-apache-spark/#respond Tue, 01 Apr 2025 09:22:20 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=57918 This 3-day instructor-led course introduces participants to the core concepts of Artificial Intelligence and Deep Learning using the Apache Spark ecosystem.

The post AI and Deep Learning using Apache Spark first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

This 3-day instructor-led course introduces participants to the core concepts of Artificial Intelligence and Deep Learning using the Apache Spark ecosystem. The training begins with foundational AI concepts, progresses to practical deep learning techniques, and culminates in distributed model training using Spark MLlib and third-party integrations such as Tensor Flow On Spark and Elephas. Through hands-on labs and real-world scenarios, participants will learn how to process large datasets, train and evaluate deep learning models in a distributed setting, and deploy them for scalable inference. By the end of the course, learners will be equipped to leverage Spark for end-to-end deep learning workflows across industries.

Duration: 3 Days

Course Code: BDT45

Learning Objectives:

After this training, participants will be able to:

Explain the fundamentals of AI and Deep Learning within the context of big data.
Compare various deep learning frameworks and their integration with Apache Spark.
Construct and train distributed deep learning models using Spark MLlib and external libraries. Evaluate the performance and scalability of deep learning models on Spark.
Deploy trained models for inference in a distributed production environment.

Basic understanding of Python and machine learning concepts
Familiarity with Apache Spark fundamentals
Prior experience with data pipelines is helpful but not required

Data scientists and engineers working with big data frameworks
AI/ML professionals interested in scalable deep learning
Developers seeking to integrate AI models in distributed environments
Analysts and architects exploring deep learning pipelines on Spark

Course Outline:

Module 1: Foundations of AI and Deep Learning

Introduction to Artificial Intelligence and Deep Learning
Key components of neural networks
Overview of big data and Apache Spark architecture
Spark MLlib for machine learning and deep learning
Comparing TensorFlow, PyTorch, and Keras with Spark integrations

Module 2: Distributed Deep Learning with Apache Spark

Deep learning workflows with Spark
Using MLlib for classification, regression, and clustering
Introduction to TensorFlowOnSpark
Hands-on: Building a neural network using Spark and Keras
Hands-on: Distributed training and tuning hyperparameters

Module 3: Scalable Deployment and Use Cases

Model evaluation and performance metrics
Exporting and saving models in Spark pipelines
Hands-on: Inference at scale with distributed models
Use case walkthroughs: Fraud detection, sentiment analysis, and image classification
Best practices for deploying AI models in production Spark clusters

The post AI and Deep Learning using Apache Spark first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/ai-and-deep-learning-using-apache-spark/feed/ 0 The Complete iOS App Development Bootcamp https://project.bigdatatrunk.com/courses/the-complete-ios-app-development-bootcamp/ https://project.bigdatatrunk.com/courses/the-complete-ios-app-development-bootcamp/#respond Wed, 20 Nov 2024 13:18:49 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=54547 This comprehensive bootcamp teaches you everything you need to know to become a proficient iOS app developer, even if you have little to no prior experience

The post The Complete iOS App Development Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

This comprehensive bootcamp teaches you everything you need to know to become a proficient iOS app developer, even if you have little to no prior experience. You'll learn to use Swift, Apple's powerful programming language, and gain hands-on experience building real-world apps with Xcode. By the end of the course, you'll be able to create professional-grade iOS applications and publish them on the App Store.

The bootcamp focuses on practical, project-based learning, covering a wide range of topics including UI/UX design, networking, data persistence, APIs, and advanced iOS features like Core Data and Core Animation. Through interactive exercises and hands-on projects, you'll gain the skills needed to build dynamic, user-friendly, and scalable iOS apps.

Duration: 8 Weeks

Course Code: BDT385

Learning Objectives:

After this course, you will be able to:

Understand the fundamentals of Swift programming language.
Build and design intuitive user interfaces using Xcode and Interface Builder.
Integrate data persistence techniques, including Core Data and UserDefaults.
Work with RESTful APIs and integrate networking in iOS apps.
Create dynamic, interactive, and visually appealing animations.
Build real-world applications with reusable and maintainable code.
Publish your apps to the App Store and manage app updates.
Develop advanced app functionalities like notifications, in-app purchases, and more.

Basic programming knowledge (preferably in Swift or any object-oriented language).
Familiarity with using macOS and Xcode is recommended but not required.

This course is designed for aspiring iOS developers, software engineers, mobile app enthusiasts, and anyone interested in learning how to build fully-functional iOS applications. It is ideal for those who want to kickstart a career in iOS app development or build their own apps for the Apple ecosystem, including iPhone and iPad.

Course Outline:

Module 1: Introduction to iOS Development & Swift Basics

Overview of iOS development ecosystem.
Setting up Xcode and an iOS project.
Introduction to Swift programming.
Variables, constants, and data types.
Control flow: If statements, loops, and functions.
Optionals and error handling.
Swift collections: Arrays, dictionaries, sets.
Introduction to SwiftUI and UIKit.

Hands-On:

Setting up a new Xcode project.
Building a simple "Hello, World" app.
Creating functions and working with variables.
Using Swift Playgrounds to practice Swift concepts.

Module 2: Building User Interfaces with Interface Builder & SwiftUI

Introduction to Interface Builder and Storyboards.
SwiftUI basics: Views, modifiers, and layouts.
Auto Layout and constraints for responsive designs.
Navigating between screens using Navigation Controllers.
Building custom UI components.
Managing UI state and data binding in SwiftUI.
Designing for different screen sizes and orientations.

Hands-On:

Building a simple calculator app.
Designing a to-do list interface using SwiftUI.
Creating a custom button with UIKit.
Implementing navigation between screens.

Module 3: Data Persistence & Core Data

Introduction to data persistence in iOS.
UserDefaults and property lists for simple data storage.
Core Data: Setting up and using Core Data.
CRUD operations with Core Data.
Data modeling and versioning.
Using SQLite and Realm as alternatives to Core Data.
Handling data migrations and performance optimization.

Hands-On:

Building a notes app using Core Data.
Saving user preferences with UserDefaults.
Implementing data storage using Realm.
Data migration in Core Data.

Module 4: Networking & APIs

Introduction to RESTful APIs and HTTP requests.
Parsing JSON data with Codable.
Using URLSession for API requests.
Working with third-party libraries like Alamofire.
Asynchronous programming with Combine and Swift Concurrency.
Caching and handling API rate limits.
Uploading data to servers.

Hands-On:

Building a weather app using a public API.
Parsing JSON data from a news API.
Uploading and downloading images from a server.
Implementing pull-to-refresh functionality.

Module 5: Advanced iOS Development Techniques

Working with Core Animation and custom transitions.
Gesture recognition and handling user interactions.
Integrating push notifications with Firebase.
In-app purchases and subscriptions.
Implementing MVVM design pattern.
Local and remote notifications.
Integrating maps and location services.

Hands-On:

Creating custom animations using Core Animation.
Building a simple game with gesture recognition.
Setting up Firebase for push notifications.
Implementing in-app purchases for a premium feature.

Module 6: Publishing to the App Store & Best Practices

Preparing your app for submission.
Creating a developer account on the Apple Developer portal.
Managing certificates and provisioning profiles.
App Store Connect: Managing app versions and metadata.
App submission process and guidelines.
Marketing your app and using analytics.
Maintaining and updating apps on the App Store.

Hands-On:

Submitting a test app to TestFlight.
Preparing app icons, splash screens, and app metadata.
Conducting beta testing with TestFlight.
Publishing an app on the App Store.

Module 7: Capstone Project & Case Studies

Project planning and wireframing.
Building a complete app from scratch, incorporating all learned concepts.
Case studies of successful iOS apps.
Code review and feedback sessions.
Preparing for iOS developer job interviews and portfolios.

Hands-On:

Building a fully functional social media app.
Case study: Rebuilding a popular app’s feature.
Mock interview sessions.
Code optimization and review.

Training Material Provided:

Comprehensive e-book on Swift and iOS development.
Sample projects and code snippets.
Access to a curated list of resources, documentation, and libraries.
Video tutorials for common development tasks.
Links to additional online resources and communities for iOS developers.

Additional Information

Software Installations Required:

Xcode: The primary development environment for iOS apps, available for free on the Mac App Store. Participants will need to install the latest version of Xcode for building and testing iOS applications.
Swift Playgrounds: A free app for iPad and macOS that makes it easy to experiment with Swift and learn coding concepts interactively.
CocoaPods/Swift Package Manager: For managing third-party libraries and dependencies within iOS projects. Participants should install CocoaPods or be familiar with using Swift Package Manager for dependency management.
Simulator Tools: Xcode comes with built-in simulators for testing apps on various iOS devices. Familiarity with using these simulators will be essential for testing app functionality.
Optional:

- Postman: A tool for testing API endpoints and HTTP requests, which can be helpful during the networking module.
- Firebase SDKs: If participants wish to use Firebase for push notifications, they will need to integrate Firebase SDKs into their Xcode projects.

Labs & Hands-On Exercises:

Labs will be conducted in each module, providing hands-on experience in iOS app development.
Each lab session will focus on implementing key concepts taught during the module, enabling participants to apply their knowledge immediately.
Participants will be required to set up their development environment (Xcode and related tools) prior to the start of the bootcamp to ensure a smooth transition into hands-on coding.

Hardware Requirements:

Mac Computer: macOS is required for Xcode, so participants need a MacBook, iMac, or Mac Mini with at least 8 GB of RAM and 10 GB of available disk space for Xcode and related tools.
iOS Device (Optional): While iOS simulators are sufficient for development, having a physical iOS device (iPhone or iPad) can help with real-world testing and deployment.

The post The Complete iOS App Development Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/the-complete-ios-app-development-bootcamp/feed/ 0 Computer Forensics Mini Bootcamp https://project.bigdatatrunk.com/courses/computer-forensics-mini-bootcamp/ https://project.bigdatatrunk.com/courses/computer-forensics-mini-bootcamp/#respond Wed, 20 Nov 2024 13:11:15 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=54543 This course provides an in-depth introduction to computer forensics, covering methods and tools for collecting, analyzing, and preserving digital evidence.

The post Computer Forensics Mini Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

This course provides an in-depth introduction to computer forensics, covering methods and tools for collecting, analyzing, and preserving digital evidence. Topics include forensic investigation processes, evidence acquisition, data recovery, file systems, and forensic analysis of Windows, Linux, and mobile devices. The course combines theory with hands-on labs, preparing participants to conduct forensic investigations and support legal cases involving digital evidence.

Duration: 5 Days

Course Code: BDT383

Learning Objectives:

After completing this course, participants will be able to:

Understand the fundamentals of computer forensics and digital evidence
Apply forensic methodologies to preserve and acquire evidence
Analyze and recover data from various file systems
Conduct forensic investigations on Windows, Linux, and mobile devices
Use industry-standard forensic tools to examine digital evidence
Generate forensic reports and support legal procedures with documentation

Basic understanding of computer systems and networks
Familiarity with operating systems, especially Windows and Linux

IT professionals, law enforcement personnel, forensic analysts, cybersecurity professionals, and anyone interested in learning digital forensics.

Course Outline:

Module 1: Introduction to Computer Forensics

Topics Covered:
- Fundamentals of Computer Forensics
- Types of Cybercrimes and Digital Evidence
- Forensic Investigation Process and Methodology
- Legal Considerations in Forensics
- Chain of Custody and Evidence Handling

Hands-On Labs:
- Setting up a forensic workstation
- Practicing chain of custody and evidence handling

Module 2: Evidence Acquisition and Preservation

Topics Covered:
- Importance of Evidence Preservation
- Imaging Techniques and Tools (e.g., FTK Imager, EnCase)
- Creating Forensic Copies (Bit-by-Bit Imaging)
- Evidence Integrity and Verification (Hashing)
- Live vs. Dead Acquisition

Hands-On Labs:
- Creating forensic images of hard drives
- Verifying images with hashing algorithms
- Live data acquisition from a running system

Module 3: File Systems and Data Recovery

Topics Covered:
- Overview of File Systems (FAT, NTFS, EXT, HFS+)
- Understanding File Structures and Metadata
- Data Recovery Techniques
- Deleted File Recovery and Carving
- Hidden and Encrypted Data

Hands-On Labs:
- Analyzing file structures in NTFS and EXT
- Recovering deleted files using forensic tools
- Data carving techniques to extract hidden files

Module 4: Windows Forensics

Topics Covered:
- Registry Analysis and Artifact Extraction
- Windows Event Logs and System Files
- Forensic Analysis of Windows Artifacts (prefetch, recycle bin, etc.)
- Analyzing User Activity (recent files, browser history)
- Memory Forensics in Windows

Hands-On Labs:
- Registry analysis for user activity tracking
- Analyzing Windows event logs
- Memory analysis to detect malicious activity

Module 5: Linux and MacOS Forensics

Topics Covered:
- Basics of Linux and MacOS File Systems
- Log File Analysis in Linux and MacOS
- User and System Activity Tracing
- Analyzing Linux Partitions and Artifacts
- Data Recovery and Forensics Tools for Linux and MacOS

Hands-On Labs:
- Analyzing log files and shell history in Linux
- Investigating user activities and file access
- Data recovery from Linux and MacOS systems

Module 6: Network Forensics

Topics Covered:
- Fundamentals of Network Forensics
- Capturing and Analyzing Network Traffic
- Intrusion Detection and Incident Response
- Tools for Network Forensics (Wireshark, Tcpdump)
- Analyzing Packet Captures (PCAP files) for Forensics

Hands-On Labs:
- Capturing network traffic with Wireshark
- Analyzing packet captures for signs of intrusion
- Identifying malicious activities in PCAP files

Module 7: Mobile Device Forensics

Topics Covered:
- Overview of Mobile Operating Systems (iOS, Android)
- Mobile Forensics Tools and Techniques
- Data Acquisition from Mobile Devices
- Analysis of Call Logs, Messages, and App Data
- Challenges in Mobile Forensics (encryption, cloud backups)

Hands-On Labs:
- Acquiring data from mobile devices
- Analyzing call logs and messages on Android
- Extracting app data for forensic analysis

Module 8: Forensic Reporting and Documentation

Topics Covered:
- Documenting Findings and Analysis
- Writing Forensic Reports for Legal Proceedings
- Presentation of Forensic Evidence
- Best Practices in Reporting and Evidence Storage
- Testifying as a Forensic Expert

Hands-On Labs:
- Preparing forensic reports using templates
- Documenting findings with screenshots and summaries
- Role-playing expert witness testimony for court preparation

Structured Labs and Case Studies

Structured Labs:
- Lab: Imaging and verifying a hard drive
- Lab: File recovery and data carving
- Lab: Registry analysis and event log analysis
- Lab: Network traffic capture and analysis
- Lab: Mobile device data acquisition
- Lab: Forensic report generation

Case Studies:
- Real-world forensic investigation scenarios for hands-on practice
- Analyzing and reporting on simulated cyber incidents

Training material provided: Yes (Digital format)

The post Computer Forensics Mini Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/computer-forensics-mini-bootcamp/feed/ 0 Incident Response Manager – Bootcamp https://project.bigdatatrunk.com/courses/incident-response-manager-bootcamp/ https://project.bigdatatrunk.com/courses/incident-response-manager-bootcamp/#respond Tue, 22 Oct 2024 10:28:37 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=54452 Welcome to the Incident Response Manager Boot Camp, a comprehensive 8-week program designed to equip participants with the skills and knowledge necessary to excel in the field of Site Reliability Engineering (SRE).

The post Incident Response Manager – Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

Welcome to the Incident Response Manager Boot Camp, a comprehensive 8-week program designed to equip participants with the skills and knowledge necessary to excel in the field of Site Reliability Engineering (SRE).

This boot camp will cover a wide range of topics, including Agile Scrum, Linux and Bash Shell scripting, Python programming, SRE principles and practical examples, DevOps with Docker and Kubernetes, SQL programming with MySQL, using MongoDB, and working with Apache Kafka stream API. Each week, you will delve into a different aspect of SRE, gradually building a strong foundation and practical experience to succeed in this critical role.

This workshop will start with Agile Scrum Methodology since the whole workshop would be executed like an Agile project. Students will then be exposed to SQL Fundamentals.

Students will then learn the basics of Linux and Bash Shell scripting, Python programming Fundamentals, and best practices. For example, students will get hands-on experience using Python libraries to manipulate data.

The course will then advance to understanding what site reliability engineering (SRE) is. Understand principles involved in SRE, what is reliability, maintainability, and availability. What type of metrics can used in SRE.

Students will gain hands-on experience by working with DevOps where they will learn about the container technology such as Docker and the orchestration of the containers using Kubernetes. Students will learn about Continuous Integration and Continuous Development (CI/CD).

Students will then learn about the differences between relational and non-relational databases. They will get a basic understanding of different NoSQL database types. After which there will be an in depth look into Document Database: MongoDB where they will learn about CRUD operations on data.

Finally, students will learn about real-time data streaming with Apache Kafka Streams API. Students will explore the architecture of Kafka and key streaming concepts. We will build data stream pipelines and learn how to debug them.

Duration: 8 Weeks

Course Code: BDT382

Understanding of how computers work
One or more years technical experience
Programming experience with Python & SQL would be a plus.

Candidates must have basic understanding of how computer systems work and have some basic understanding of computer programming.

Course Outline:

Agile Scrum Methodology

Scrum Introduction
Scrum Team
Scrum Artifacts
Sprint Increment
Spring planning
Backlog
Retrospective
Project description and Case Study
Practice exam and Knowledge check
Certification (optional)

Structured Query Language (SQL)

Working with SQL
1. SQL Fundamentals
2. Writing SQL Queries
3. Working Tables and Indexes
4. Predefined SQL functions
5. Connecting Python to SQL
6. Certification (optional)

Linux & Bash Scripting

Working with Linux
1. File System and Access
2. Linux Fundamentals
3. System Administration Basics
4. Hands-on with Bash Shell Scripting
5. Networking Services
6. Internet protocols such as HTTP, TCP/UDP

Python Programming – Fundamentals

Set up
1. Set up development environment – Visual Studio Code
2. Using python shell
3. Executing python script
4. Understanding python strings
5. Print statements in python
Data Structures in python
1. Integers
2. Lists
3. Dictionaries
4. Tuple
5. Sets
6. File
7. Mutable and Immutable structures
Selection and Looping Constructs
1. If/else/elif statements
2. Boolean type
3. “in” membership
4. For loop
5. While Loop
6. List and Dictionary Comprehension
Functions
1. Defining functions
2. Variable scope – Local and Global
3. Arguments
4. Polymorphisms
Modules
1. Creating modules
2. Importing Modules
3. Different types of imports
4. Dir and help
5. Examining some built-in modules

ITIL Foundation & ITSM

Introduction to ITIL 4 Foundation
Framework Terminology and Structure
Introduction to Service Management
The principles underlying service management
The Four Dimensions of Service Management
The approach and guidelines: Service Value System
Service Value Chain
7 practices
- Continuous Improvement
- Change Control
- Incident Management
- Problem Management
- Service Request Management
- Service Desk
- Service Level Management

Site Reliability Engineering (SRE) Basics:

Introduction to SRE
1. What is SRE?
2. Reliability, Maintainability & Availability
3. SRE principles
Understanding SRE principles
1. Seven principles of SRE
2. Service level objectives
3. Monitoring
4. Automation
5. Release Engineering
6. Root cause analysis
7. Testing and releasing
8. Capacity planning
SRE Role
1. What is a site reliability engineer?
2. What does SRE do?
3. Adopting SRE and SRE Team Formats

DevOps Essentials:

Introduction to DevOps
1. What is DevOps?
2. Goals of DevOps
3. DevOps benefits
4. Collaboration and Culture in DevOps
Version Control with Git
1. Importance and need of version control
2. Version Control Options
3. Git Overview
4. Setting up Git and repositories
5. Using Git Commands
6. Git workflows
Continuous Integration & Deployment (CI/CD)
1. Introduction to CI/CD
2. Continuous Integration Pipelines
3. Setting up CI/CD pipeline
4. Continuous Integration with tools like Jenkins & GitHub
Best practices in DevOps

General Technology Support Basics:

Server: Administration and troubleshooting in Linux and Windows as well as patching and basic scripting skills (PowerShell, Bash)
Converged Solutions: VMWare platform and network connectivity, and patching, alongside PowerShell and Linux scripting skills
Storage Overview: CIFS/NFS, Linux and Windows scripting, DPA reporting, Avamar and Data Domain administration, and solid understanding of Windows and Linux environments
Middleware Basics: Linux, Windows, WebSphere, Apache, IIS, WebLogic and Tomcat
Mainframes: JCL, CICS SYSPLEX
Networking: Strong understanding of the network protocols and OSI Model
Collaboration Tools: TrueSight, Jira, and Confluence
General understanding of technologies. Big Panda, Log scale, Dynatrace, MLOps

Project & Use Case

Project Overview
Complete projects to get experience and practice.
Industry Use Case Studies

Certification

Certification Overview
Identify the right certification for you.
Tips to prepare for certification.

The post Incident Response Manager – Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/incident-response-manager-bootcamp/feed/ 0 Network Engineer – Bootcamp https://project.bigdatatrunk.com/courses/network-engineer-bootcamp/ https://project.bigdatatrunk.com/courses/network-engineer-bootcamp/#respond Tue, 06 Aug 2024 06:42:08 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=53267 Welcome to the Network Engineer Boot Camp, an immersive 8-week program designed to provide an in-depth exploration of networking principles and practices. This boot camp is tailored to equip students with a thorough understanding of both fundamental and advanced networking concepts.

The post Network Engineer – Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

Welcome to the Network Engineer Boot Camp, an immersive 8-week program designed to provide an in-depth exploration of networking principles and practices. This boot camp is tailored to equip students with a thorough understanding of both fundamental and advanced networking concepts.

The program begins with an introduction to Agile Scrum Methodology, framing the entire course as an Agile project to simulate real-world project management practices. Students will gain foundational knowledge in Agile Scrum, which will be applied throughout the boot camp to enhance their learning experience.

Following this, students will build essential skills in Linux and Bash Shell scripting, setting a solid groundwork for understanding and managing network systems. The core focus then shifts to comprehensive networking education, covering a wide array of topics including the OSI model, network devices, IP addressing, subnetting, VLANs, VPNs, QoS, SDN, TCP and UDP protocols, routing protocols, and network management.

In addition to networking fundamentals, the boot camp includes practical, hands-on experience with DevOps practices. Students will explore container technology using Docker and orchestrate containers with Kubernetes, gaining valuable insights into Continuous Integration and Continuous Deployment (CI/CD) processes.

This program combines theoretical knowledge with practical application, ensuring that students are well-prepared to design, implement, and manage complex network infrastructures and effectively leverage modern DevOps practices.

Duration: 8 weeks

Course Code: BDT365

Understanding of how computers work
One or more years technical experience
No prior networking experience required

Aspiring network engineers and administrators
IT professionals seeking to enhance their networking skills
Students and recent graduates interested in networking
Individuals aiming to gain a comprehensive understanding of network technologies

Course Outline:

Agile Scrum Methodology

Scrum Introduction
Scrum Team
Scrum Artifacts
Sprint Increment
Spring planning
Backlog
Retrospective
Project description and Case Study
Practice exam and Knowledge check
Certification (optional)

Linux & Bash Scripting

1. Working with Linux

File System and Access
Linux Fundamentals
System Administration Basics
Hands-on with Bash Shell Scripting
Networking Services

Python Programming – Fundamentals

1. Set up

Set up development environment – Visual Studio Code
Using python shell
Executing python script
Understanding python strings
Print statements in python

2. Data Structures in python

Integers
Lists
Dictionaries
Tuple
Sets
File
Mutable and Immutable structures

3. Selection and Looping Constructs

If/else/elif statements
Boolean type
“in” membership
For loop
While Loop
List and Dictionary Comprehension

4. Functions

Defining functions
Variable scope – Local and Global
Arguments
Polymorphisms

5. Modules

Creating modules
Importing Modules
Different types of imports
Dir and help
Examining some built-in modules

Networking Fundamentals:

1. Network Basics

Introduction to fundamental networking concepts
Different types of networks
Basic Network Functions

2. Network Architectures (OSI Model)

Detailed exploration of the OSI (Open Systems Interconnection)
The seven layers (Physical, Data Link, Network, Transport, Session, Presentation and Application)
Understand how each layer functions and interacts within a network

3. What are Hubs, Switches and Router?

Examine roles and functions of networking devices such as hubs, switches and routers in a network
Differences in their operations
How these devices facilitate network communication and connectivity

4. Data Forwarding Through a Network

Gain insight into data forwarding process within a network
Overview of data encapsulation, packet switching, and role of MAC addresses and IP addresses in data transmission

5. IP Addresses

Introduction to IP addressing, includes the structure of IPv4 and IPv6 addresses
Understand how IP addresses identify devices on a network and facilitate communication

6. IP Subnetting

Detailed instruction on subnetting IPv4 addresses, including calculating subnet masks and understanding subnetting notations
Practice in designing and implementing sub-netted IP address schemes

7. Cabling and Network Topologies

Overview of different types of network cables (e.g. twisted pair, coaxial, fiber, optic) and their uses
Understand different types of network topologies (star, ring, mesh) and their implications for network design and performance

8. TCP and UDP Protocols

Exploration of TCP (Transmission Control Protocol) and UDP (User Datagram Protocol)
Their differences and respective uses
Understand how these protocols manage data transmission and ensure reliable communication

9. DNS and DHCP

Introduction to Domain Name Service (DNS) and Dynamic Host Configuration Protocol (DHCP)
Understand how DNS resolves domain names to IP addresses
How DHCP automates IP address assignment to devices on a network

10. Routing

Overview of routing principles and techniques
Different routing protocols: static, RIP, OSPF
Understand concepts such as routing tables, forwarding tables and path selection

11. VLANs

Understanding Virtual Local Area Networks (VLANs), its purpose and benefits
Configuration and management of VLANs, including inter-VLAN routing and VLAN tagging

12. ACLs (Access Control Lists)

Explanation of ACLs for network security and traffic management
Types of ACLs (standard and extended) and their using in filtering network traffic based on IP addresses and protocols

13. Network Naming

Introduction to network naming conventions, including host name assignment and domain naming
How names are resolved into IP addresses and the role of naming in network management

14. Quality of Service (QoS)

Fundamentals of Quality of Service (QoS) and its roles in managing network traffic
Techniques for prioritizing different types of traffic to ensure optimal performance for critical applications

15. Network Time Protocol (NTP)

Overview of network time protocol (NTP)
Configuring NTP

16. Port SPAN (Mirroring)

SPAN network overview
Configuring SPAN and Ingress options

17. Network Address Translation (NAT)

Overview of NAT and its role in managing IP address allocation and conserving address space
Understanding different types of NAT (static, dynamic, PAT)
Impact on NAT on network security and connectivity

18. Network Management

Purpose of network management
Types of Network Protocols used (Query based, Event Based)
Using Simple Network Management Protocol (SNMP)

19. IPv6

Configuring IPv6 addresses
Understanding IPv6 addressing and routing

20. Virtual Private Network (VPN)

Introduction to VPN technologies including their purpose in providing secure remote access and protecting data over public networks
Overview of VPN protocols such as IPsec, SSL, GRE

21. Software Defined Networking (SDN)

Introduction to Software Defined Networking (SDN) and its impact on network architecture and management
Overview of SDN principles, benefits, and how it differs from traditional networking models

DevOps:

1. Introduction to DevOps

What is DevOps?
Goals of DevOps
DevOps benefits
Collaboration and Culture in DevOps

2. Continuous Integration & Deployment (CI/CD)

Introduction to CI/CD
Continuous Integration Pipelines
Setting up CI/CD pipeline
Continuous Integration with tools like Jenkins & GitHub

3. Best practices in DevOps

Containerization & Orchestration:

1. Containers with Docker

Introduction to Containers
Docker overview
Docker commands
Understanding Dockerfile
Building Docker Containers
Using Docker compose for building & testing software

2. Container Orchestration with Kubernetes

Introduction to Kubernetes
Kubernetes Architecture & Clusters
Deploying Applications with Kubernetes
Scaling & Load balancing with Kubernetes
Kubernetes networking
Service discovery in Kubernetes
Rolling updates & rollbacks
Service meshes

Project & Use Case

Project Overview
Complete projects to get experience and practice
Industry Use Case Studies

Certification

Certification Overview
Identify the right certification for you
Tips to prepare for certification

The post Network Engineer – Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/network-engineer-bootcamp/feed/ 0 Business UAT – Bootcamp https://project.bigdatatrunk.com/courses/business-uat-bootcamp/ https://project.bigdatatrunk.com/courses/business-uat-bootcamp/#respond Tue, 21 May 2024 07:28:13 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=52604 In this immersive 6-week Business UAT Bootcamp, students will master the essential skills and tools needed for success in the dynamic world of software testing.

The post Business UAT – Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

In this immersive 6-week Business UAT Bootcamp, students will master the essential skills and tools needed for success in the dynamic world of software testing. From Agile Scrum methodologies to comprehensive SDLC understanding, the bootcamp will equip students with testing fundamentals and specialized Business UAT techniques. Students will explore testing tools like JIRA, HP ALM, and TestRail, and hone their abilities to manage, execute, and report on tests efficiently. The Capstone project will enhance student learning with a hands-on project, to jump start their careers as proficient Business UAT Testers.

Course Code – BDT345

Duration: 6 Weeks

Learning Objectives:

Understand the principles and practices of Agile methodologies, particularly Scrum, and their application in software development projects.
Gain comprehensive knowledge of the Software Development Life Cycle (SDLC), including its various phases and the role of User Acceptance Testing (UAT) within the SDLC.
Develop proficiency in testing fundamentals, including different testing types, test case design techniques, test planning, execution, and reporting.
Acquire specialized skills in Business UAT testing, including requirements gathering, test case creation, test execution, defect management, and stakeholder communication.
Get familiarity with essential testing tools such as JIRA, HP ALM, and TestRail, and learn how to effectively utilize them for test management, defect tracking, and reporting.
Apply theoretical knowledge and practical skills acquired throughout the bootcamp to real-world scenarios through a capstone project, demonstrating the ability to effectively plan, execute, and manage UAT activities within an Agile development environment.

Basic Understanding of Software Development
Analytical and Problem-solving skills with an eye on detail
Basic Computer Skills

Candidates with Bachelor’s in Computer Science or equivalent experience
Pursuing roles focused on Quality Testing
Eagerness to learn.

Course Outline:

Software Development Lifecycle (SDLC)

Types of SDLC methodologies
Understanding the impact on testing
Roles and responsibilities
Role of UAT in SDLC
Integration of UAT with other phases
Case study of successful team(s) delivering high quality product

Agile Scrum Methodology

Scrum Introduction
Scrum Team
Scrum Artifacts
Sprint Increment
Spring planning
Backlog
Retrospective

Testing Fundamentals

Overview of QA (what/why/benefits)
QA roles and responsibilities
Career Growth in QA
Test Management overview
Understanding the cycles and purposes of testing
Types of testing
Test design overview
Writing good bugs
What to measure (metrics for QA)
Webapp Testing
Mobile Testing
Firmware Testing
Regression testing
Frequently used tools overview
Test / Release / Deploy QA overview
Test documentation: test cases, test scenarios, test scripts
Hands-on exercises

Business UAT Testing

UAT Process Overview
Understanding Business Need
Understanding the role of a Business UAT Tester
Identifying stakeholders and gathering requirements
Acceptance test planning
Performing UAT
Writing UAT test cases
Techniques for writing clear and concise test cases
Test execution planning for UAT
Setting up UAT test environments
Executing UAT test cases and scenarios
Test execution strategies: manual vs. automated testing
Test execution environments and configurations
Test reporting: documenting test results, defect tracking
Managing test execution and defects
Best practices for conducting UAT
Common UAT Challenges
Science of Effective UAT
UAT walkthroughs and reviews
Stakeholder communication and collaboration during UAT

Tools

Introduction to testing tools
JIRA
HP ALM (Application Lifecycle Management)
TestRail

Capstone Project

Applying Agile principles, SDLC knowledge, testing fundamentals, and UAT techniques learned throughout the bootcamp
Deliverables include UAT test plan, test cases, test execution reports, and defect logs
Presentation of the project to the class.

The post Business UAT – Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/business-uat-bootcamp/feed/ 0 Cyber Security – Bootcamp https://project.bigdatatrunk.com/courses/cyber-security-bootcamp/ https://project.bigdatatrunk.com/courses/cyber-security-bootcamp/#respond Tue, 13 Feb 2024 04:34:52 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=50745 Welcome to the Cybersecurity Boot Camp, a comprehensive 8-week program designed to equip participants with the skills and knowledge necessary to excel in the field of Cyber Security.

The post Cyber Security – Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

Welcome to the Cybersecurity Boot Camp, a comprehensive 8-week program designed to equip participants with the skills and knowledge necessary to excel in the field of Cyber Security.

This boot camp will cover a wide range of topics related to cyber security such as access controls, network security, security operations. Students will get an understanding of Business Continuity Planning, Disaster Recovery Planning, and Incident Response Concepts. Learn about physical and logical access controls for an organization. Understand the concepts behind Confidentiality, Integrity, and Availability (CIA Triad) and handling risk management.

Immerse yourself in the dynamic realm of cybersecurity through real-world simulations, practical exercises, and a specialized focus on the CompTIA Cybersecurity Analyst (CYSA+) certification.

Students will then learn about network security including various types of attacks. There will be hands-on sessions for some of these topics. Understand security operations such as patch, configuration, change management.

This workshop will start with Agile Scrum Methodology since the whole workshop would be executed like an Agile project.

Students will then learn the basics of Linux and Bash Shell scripting, Python programming Fundamentals, and best practices.

Duration: 8 weeks

Course Code: BDT326

Understanding of how computers work
One or more years technical experience
Programming experience with Python & SQL would be a plus.

Candidates must understand how computer systems work and have some basic understanding of computer programming.

Course Outline:

Agile Scrum Methodology

Scrum Introduction
Scrum Team
Scrum Artifacts
Sprint Increment
Spring planning.
Backlog
Retrospective
Project description and Case Study
Practice exam and Knowledge check.
Certification (optional)

Python Programming – Fundamentals

Set up

Set up development environment – Visual Studio Code
Using python shell
Executing python script
Understanding python strings
Print statements in Python.

2.Data Structures in python

Integers
Lists
Dictionaries
Tuple
Sets
File
Mutable and Immutable structures

3.Selection and Looping Constructs

If/else/elif statements
Boolean type
“in” membership
For loop
While Loop
List and Dictionary Comprehension

4.Functions

Defining functions
Variable scope – Local and Global
Arguments
Polymorphisms

5.Modules

Creating modules
Importing Modules
Different types of imports
Dir and help
Examining some built-in modules

SQL

SQL Fundamentals
Writing SQL Queries
Working Tables and Indexes
Predefined SQL functions
Uses for SQL
A/C/I/D
Data Models
Database Terminology
Normalization
First, Second & Third Normal Forms
ANSI SQL
Standardization & SQL Dialects
DDL, DML, DTL, DQL, and DCL
Data Integrity
Types of Integrity
Constraints
Data Types
Triggers
What are Joins?
Join Syntax
Join Predicates
Types of Joins
The ‘using’ keyword

Core Linux Fundamentals:

1. Basic Linux Tasks

Linux and its history
CLI and Shell
Bash commands
Man pages & other help resources

2.Users and Groups

What are users and groups?
Create, Modify and Delete users
Create, Modify and Delete user groups
Account profiles

3.File Permissions & Ownership

File & Directory ownership
Modifying permissions
Special permissions and attributes

4.Storage

Storage partitions
Creating partitions
Volumes and their management
Mounting file systems
Linux Directory structure

5.Files and Directories

Working with text files
Searching files
Manipulating file outputs

6.Kernel Modules

What are kernel modules
The Linux Kernel
Installing and Configuring Kernel modules
Monitoring kernel modules

7.Linux Boot Process

Linux boot process
Linux boot components
GRUB and configuring it

8.System Components

Linux system components
Localization options
GUI
Services
CPU and Memory issues

9.Devices

What are Linux devices?
Configuring and Monitoring devices

10.Networking

Linux server roles
Connecting to a network
Configuring network identity
DHCP & DNS
Cloud Technologies
Virtualization technologies

11.Packages and Software

Package managers
Repositories

12.Securing Linux Systems

Securing Linux Systems
Cybersecurity best practices
Encrypting Volume
Configuring SSH
Firewalls and configuring them
Logging Services
Backup, Restore and Verify data
Compressing files

13.Bash Scripting

Understanding shell scripting
Bash shell fundamentals
Scripting and programming
Control statements

14.Task Automation

What is task automation?
Scheduling jobs
Scheduling tasks
Version Control System (Git)

Cyber Security Fundamentals:

1. Security Principles

Why Cybersecurity?
Information security vs IT security vs Cybersecurity
Privacy
Basic Cybersecurity Terms
Understanding CIA Triad
Identity and Access Management
Risk Management
Access Control Categories
Governance vs Management

2. Business Continuity Plan, Disaster Recovery Plan, and Incidence Response

Business Continuity Planning – what it is and what is involved?
Disaster Recovery Planning – purpose and objectives, MOR, MTD
Incidents Response – monitoring & detection of security events

3. Access Control

Physical Security = what is involved?
Perimeter Defense
Logical Access Control
Central vs Decentralized Logical Access Controls
Access Control: RBAC, ABAC, DAC

4. Network Security - I

Network Basics and Definitions
The OSI Model
The TCP Model
IP address, port number and MAC address
IP protocols: SSL/TLS, IPSec, VPNs, SSH
NAT: Network Address Translation
Wireless networks

5. Network Security - II

Understanding VLANs and Routers
Software Defined Networks (SDNs)
Attacks & Hackers
Intrusion Detection & Prevention Systems (IDS-IPS)
Firewalls and Next Generation firewalls
Virtualization, Cloud and Distributed Computing
Fault Tolerance
Secure Design Principles

6. Variety of Attacks

1. Port scanning and firewalls

2. Hacker Attacks

Password Attacks
DoS and DDoS
Network Attacks
Man in the middle attack
Social Engineering

3. Web Application Security

SQL Injection
Blind SQL injection
Mitigating SQL injection attacks
Vulnerability Management

4. Malware

Introduction
Viruses and Worms
Trojans
Spyware, Adware and Ransomware
Logic Bombs and Rootkits
Antimalware

Security Operations

Configuration Management
Patch Management
Change Management
Cryptography & Hashing
Data handling, data storage and data retention
Training and Awareness
Social Engineering attacks

8. Wireshark

When to use a network sniffing tool,
Complete basic configurations on the tool.
Manipulate data in the application.
Identify various traffic flows and protocols.
Extract data and files from a PCAP Files
Create a cyber incident Report.

Cloud Security

Cloud Computing
Shared Responsibility
SASE (Secure Access Service Edge)

AI, Quantum Computing

AI (Artificial Intelligence)
Impact of AI on Cybersecurity
Leveraging AI for security
Quantum Computing and its impact on Cybersecurity

11. Laws, Regulations and Standards

Factors Affecting the Regulations
Widely Adopted Regulations (HIPAA, GDPR, CCPA, etc.)
Compliance Frameworks (NIST, ISO, etc.)

Cybersecurity Tools

Categories of Tools
Selection of Tools

Continuous Integration & Continuous Deployment (CI/CD):

1. Introduction to CI/CD

Introduction to CI/CD
Continuous Integration, Continuous Delivery, Continuous Deployment
Continuous Integration pipelines
Creating pipelines
Automating Deployments

Project & Use Case

Project Overview
Complete projects to get experience and practice.
Industry Use Case Studies

Certification

Certification Overview
Identify the right certification for you.
Tips to prepare for certification.

The post Cyber Security – Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/cyber-security-bootcamp/feed/ 0 Site Reliability Engineering Bootcamp https://project.bigdatatrunk.com/courses/site-reliability-engineering-bootcamp/ https://project.bigdatatrunk.com/courses/site-reliability-engineering-bootcamp/#respond Fri, 08 Dec 2023 10:31:23 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=48719 Welcome to the Site Reliability Engineering Boot Camp, a comprehensive 10-week program designed to equip participants with the skills and knowledge necessary to excel in the field of Site Reliability Engineering (SRE).

The post Site Reliability Engineering Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

Welcome to the Site Reliability Engineering Boot Camp, a comprehensive 10-week program designed to equip participants with the skills and knowledge necessary to excel in the field of Site Reliability Engineering (SRE).

This workshop will start with Agile Scrum Methodology since the whole workshop would be executed like an Agile project. Students will then be exposed to SQL Fundamentals.

Duration: 10.5 weeks

Course Code: BDT320

Understanding of how computers work
One or more years technical experience
General Programming experience with Python
Rudimentary knowledge of Networking Concepts.

Candidates must have basic understanding of how computer systems work and general knowledge of networking concepts and computer programming.

Course Outline:

Professional Business Skills (3 days)

Personal Development
Personality Assessment (1 hour)
Psychological Safety (1 hour)
Growth Mindset (1 hour)
Emotional Intelligence (1 hour)
Crash Course: Productivity and Time Management (2 hours)

Culture and the Team

Team vision, mission and values (1.5 hours)
Managing team conflict (30 min)
Celebrating failures (30 min)
Meeting facilitation (1 hour)

Communication

Written and Verbal Communication (1.5 hour)
Asking Better Questions (2 hours)
Managing difficult conversations (1.5 hours)
Giving and receiving feedback (1 hour)
Introduction to Design Thinking (2 hours)

Agile Scrum Methodology

Scrum Introduction
Scrum Team
Scrum Artifacts
Sprint Increment
Spring planning
Backlog
Retrospective
Project description and Case Study
Practice exam and Knowledge check
Certification (optional)

Structured Query Language (SQL)

Working with SQL
SQL Fundamentals
Writing SQL Queries
Working Tables and Indexes
Predefined SQL functions
Connecting Python to SQL
Certification (optional)

Linux & Bash Scripting

Working with Linux
File System and Access
Linux Fundamentals
System Administration Basics
Hands-on with Bash Shell Scripting
Networking Services
Internet protocols such as HTTP, TCP/UDP

Python Programming – Fundamentals

Set up
Set up development environment – Visual Studio Code
Using python shell
Executing python script
Understanding python strings
Print statements in python

Data Structures in Python

Integers
Lists
Dictionaries
Tuple
Sets
File
Mutable and Immutable structures

Selection and Looping Constructs

If/else/elif statements
Boolean type
“in” membership
For loop
While Loop
List and Dictionary Comprehension

Functions

Defining functions
Variable scope – Local and Global
Arguments
Polymorphisms

Modules

Creating modules
Importing Modules
Different types of imports
Dir and help
Examining some built-in modules

Site Reliability Engineering (SRE) Fundamentals

Introduction to SRE

What is SRE?
Reliability, Maintainability & Availability
SRE principles

Understanding SRE Principles

Seven principles of SRE
Service level objectives
Monitoring
Automation
Release Engineering
Root cause analysis
Testing and releasing
Capacity planning

Understanding Reliability

What is reliability?
Life cycle of reliability
Understanding failure and failure rates
Understanding MTTR, MTTD, MTTF and MTBF

Maintainability

What is maintainability?
Life cycle of maintainability
Up time and down times
Preventive maintenance
Maintainability costs, predictions, and requirements

Availability

Introduction to Availability
Inherent Availability
Operational Availability
Achieved Availability
Monitoring tools such as Dynatrace

SRE Role

What is a site reliability engineer?
What does SRE do?
Adopting SRE and SRE Team Formats

DevOps

Introduction to DevOps
What is DevOps?
Goals of DevOps
DevOps benefits
Collaboration and Culture in DevOps

Version Control with Git

Importance and need of version control
Version Control Options
Git Overview
Setting up Git and repositories
Using Git Commands
Git workflows

Continuous Integration & Deployment (CI/CD)

Introduction to CI/CD

Continuous Integration Pipelines
Setting up CI/CD pipeline
Continuous Integration with tools like Jenkins & GitHub

Best practices in DevOps

Containerization & Orchestration

Containers with Docker
Introduction to Containers
Docker overview
Docker commands
Understanding Dockerfile
Building Docker Containers
Using Docker compose for building & testing software.

Container Orchestration with Kubernetes

Introduction to Kubernetes
Kubernetes Architecture & Clusters
Deploying Applications with Kubernetes
Scaling & Load balancing with Kubernetes
Kubernetes networking
Service discovery in Kubernetes
Rolling updates & rollbacks
Service meshes

Continuous Integration & Continuous Deployment (CI/CD)

Introduction to CI/CD
Introduction to CI/CD
Continuous Integration, Continuous Delivery, Continuous Deployment
Continuous Integration pipelines
Creating pipelines
Automating Deployments

Document Datastore: MongoDB

Working with SQL

MongoDB Introduction
Understanding Basics and CRUD operations
Structuring Documents
Create Operations
Read Operations on Collections
Updating Documents
Deleting Documents
Working with Indexes
Working with different data types
Using MongoDB Compass to explore data visually.

Apache Kafka Event Streaming

Understanding Apache Kafka Streams

Understanding different ways of using Apache Kafka
Working with Kafka Streams
Operators in Kafka streams using KStream API
Serialization & Deserialization in KStreams

KTable & Global KTable

What is KTable?
What is a Global KTable?
Building a topology for KTable

Stateful operations in KStreams

Aggregation and how it works?
Using count, reduce and aggregate.
Performing KStream Joins

Project & Use Case

Project Overview
Complete projects to get experience and practice.
Industry Use Case Studies

Certification

Certification Overview
Identify the right certification for you.
Tips to prepare for certification.

The post Site Reliability Engineering Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/site-reliability-engineering-bootcamp/feed/ 0 Business Competency (Fraud Analyst) – Bootcamp https://project.bigdatatrunk.com/courses/business-competency-fraud-analyst-bootcamp/ https://project.bigdatatrunk.com/courses/business-competency-fraud-analyst-bootcamp/#respond Thu, 26 Oct 2023 06:40:38 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=45276 The Business Competency (Fraud Analyst) Bootcamp is an intensive 10-week program designed to equip participants with essential skills and knowledge in various competencies crucial for success in the business world.

The post Business Competency (Fraud Analyst) – Bootcamp first appeared on Big Data Trunk.

]]>

Overview
Prerequisites
Audience
Curriculum

Description:

The Business Competency (Fraud Analyst) Bootcamp is an intensive 10-week program designed to equip participants with essential skills and knowledge in various competencies crucial for success in the business world.

The bootcamp will focus on specific business-related topics such as business analytics, process management, and risk assessment.

Throughout the bootcamp, participants will be engaged in a wide range of learning activities, including interactive lectures, hands-on projects, group discussions, and real-world case studies. Industry experts, seasoned professionals, and renowned educators will guide participants, ensuring a high-quality and relevant learning experience.

The Business Competency Bootcamp promises an immersive and transformative learning experience, empowering participants to become adept decision-makers, effective communicators, and valuable assets in their professional spheres. Participants will emerge with a well-rounded skill set, prepared to tackle complex business challenges, and seize opportunities for success.

By the end of the program, participants will be better equipped to make informed decisions, solve complex business problems, and contribute effectively to their organizations.

Duration:10 weeks

Course Code: BDT319

Basic knowledge of business principles and terminology
Familiarity with Microsoft Office suite (Word, Excel, PowerPoint)
Strong desire to enhance analytical, problem-solving, and decision-making skills

The bootcamp is designed for professionals, recent graduates, and individuals seeking to enhance their business competencies and advance their careers. Participants should have a basic understanding of business concepts and terminology.

High Level Curriculum:

Building the Foundation

Introduction to Business Competency Bootcamp
Understanding Analytical Thinking
Root Cause Analysis Techniques
Introduction to Business Acumen
Business Intelligence and Data Visualization Tools

Empowering Business Insights

Advanced Statistical Analysis for Decision Making
Introduction to Business Analytics
Data Collection and Preparation Techniques
Consulting Skills and Client Relationship Building

Effective Communication and Customer Focus

Effective Communications in Business
Decision-Making Process and Critical Thinking Strategies
Addressing Customer Needs and Customer-Centric Approaches
Business Assessment and Opportunity Evaluation

Harnessing Business Data and Processes

Business Data Analysis Techniques
Information Capture and Document Management
Modeling: Data, Process, Events, Objects
Process Management and Business Process Improvement

Strategies for Success

Requirements Analysis and Gathering
Software Product Business Knowledge and Market Analysis
Introduction to Project Management
Workflow Analysis and Automation

Navigating Compliance and Risk

Anti-money Laundering/Sanctions Policies and Procedures
Business Ethics and Ethical Decision Making
Fraud Detection and Prevention Strategies
Operational Risk Management

Problem-Solving and Operational Efficiency

Problem Solving Approaches and Tools
Standard Operating Procedures and Business Process Documentation
Applying Business Analytics in Decision Making
Communication in Consultancy and Effective Client Presentations

Culmination and Future Success

Capstone Project: Applying Competencies to Real-World Scenarios
Review and Assessment of Competency Learning
Closing Ceremony and Certificate Distribution

Please note that the curriculum is designed to provide a comprehensive overview of the topics covered in the Bootcamp. The actual content and specific tools used may vary based on the expertise of the instructors and the latest industry trends.

Learning Topics:

SDLC (Software Development Life Cycle)

Software Engineering – Intro
SDLC
Various phases in detail
Models
Waterfall
Spiral
Prototyping
Agile
Software metrics (Size, FP)

Agile Scrum Methodology

Scrum Introduction
Scrum Team
Scrum Artifacts
Sprint Increment
Spring planning
Backlog
Retrospective
Project description and Case Study
Practice exam and Knowledge check
Certification (optional)

Business Analyst Competency

Introduction to Business Analysis:
- Understanding the role of a business analyst
- Key responsibilities and tasks of a business analyst
- The value of business analysis in different industries
Requirements Gathering and Elicitation:
- Techniques for gathering business requirements
- Conducting stakeholder interviews and workshops
- Documenting and managing requirements effectively
Business Process Analysis:
- Understanding and mapping business processes
- Identifying process improvements and optimizations
- Analyzing process efficiency and effectiveness
Project Management for Business Analysts:
- Basics of project management methodologies (e.g., Agile, Waterfall)
- Collaborating with project teams and stakeholders
- Managing project scope and handling change requests
Systems and Software Analysis:
- Analyzing existing systems and software
- Identifying gaps and opportunities for improvement
- Participating in the selection and implementation of new systems
Use Case Development:
- Creating use cases and user stories
- Defining functional and non-functional requirements
- Prioritizing and managing requirements in a dynamic environment
Business Analysis Tools:
- Introduction to popular business analysis tools (e.g., JIRA, Confluence, Microsoft Visio)
- Utilizing tools for requirement management and collaboration

SQL Essentials

SQL Fundamentals
Writing SQL Queries
Working Tables and Indexes
Predefined SQL functions

Uses for SQL
A/C/I/D
Data Models
Database Terminology
Normalization
First, Second & Third Normal Forms
ANSI SQL
Standardization & SQL Dialects
DDL, DML, DTL, DQL, and DCL
Data Integrity
Types of Integrity
Constraints
Data Types
Triggers
What are Joins?
Join Syntax
Join Predicates
Types of Joins
The ‘using’ keyword

Descriptive Statistics Fundamentals

Central Tendency
- Mean
- Median
- Mode
Spread of the Data
- Variance
- Standard Deviation
- Range
Relative Standing
- Percentile
- Quartile
- Inter-quartile Range

Inferential Statistics Fundamentals

Inferential Statistics
- Normal Distribution
- Central Limit Theorem
- Standard Error
- Confidence Intervals
- Other Distributions
- Samples
- Hypothesis Testing
Perform statistical analysis on a given data set.

Data Exploration and Preparation

Data Exploration
- Describe
- Merging
- Grouping
- Evaluating Features
Data Visualization
- Line Chart
- Scatterplot
- Pairplot
- Histogram
- Density Plot
- Bar Chart
- Boxplot
- Customizing Charts
Perform Exploratory Data Analysis
Data Cleaning
- Dropping Rows
- Imputing Missing Values
- Feature Evaluating

Data Storytelling

Drafting the Story
Information Hierarchy
Story telling
Visual Presentation
Interactivity

Data Visualization using Tableau

Data Analysis lifecycle and Tableau’s role in the data analysis world
Introduction to Tableau tool
Features and Functionalities of Tableau
Connection to excel datasheet work on Union and Joins
Connection to excel datasheet to create our first graph
Perform Sorting, Filtering, Grouping of the data in the report
Utilize the Marks card and Pages card in the visualization area
Use Aggregate Measures / create trend lines / discuss the data plot in the report
Create multiple graphs based on the data and requirement of the scenarios
Create a dashboard with multiple graphs / reports included in
Create our own story in a way to present to executives / senior managers
Connect to additional data source and switch the session while doing hands on
Perform all the above operations with the trainer during the session
Hands-on exercise 1 – Create Bar / Line / Trend / Pie graphs during training
Hands-on exercise 2 – Create Dashboards in Tableau, explore presentation and share options
Hands-on exercise 3 – Create Story to present in Tableau

Generative AI Essentials

Introduction to Generative AI
Prompt Engineering
Do’s and Don’ts of Generative AI
Applications of Generative AI

Navigating Compliance and Risk

Anti-Money Laundering (AML) and Sanctions Policies:
- Understanding AML and its importance in the financial industry
- Recognizing the risks and consequences of money laundering
- Overview of international sanctions and their implications
Regulatory Framework and Compliance Requirements:
- Familiarization with key financial regulations and compliance standards
- Compliance requirements for financial institutions and businesses
- Role of compliance officers and compliance departments
KYC (Know Your Customer) and Customer Due Diligence:
- Importance of KYC procedures in customer onboarding
- Conducting customer due diligence to assess risk levels
- Identifying red flags and suspicious activities
Transaction Monitoring and Suspicious Activity Reporting:
- Implementing transaction monitoring systems for suspicious patterns
- Understanding the process of filing Suspicious Activity Reports (SARs)
- Compliance responsibilities in reporting suspicious activities
Risk Assessment and Risk Management:
- Conducting risk assessments to identify potential vulnerabilities
- Evaluating risk exposure in different business operations
- Developing risk management strategies and controls
Fraud Detection and Prevention:
- Techniques for detecting fraudulent activities
- Fraud prevention strategies and best practices
- Role of technology in fraud detection and prevention
Operational Risk Management:
- Identifying operational risk factors in business processes
- Strategies to mitigate and manage operational risks
- Incident response and business continuity planning
Compliance Audits and Internal Controls:
- Importance of compliance audits in ensuring adherence to regulations
- Establishing effective internal controls to minimize risks
- Role of internal auditors in evaluating compliance effectiveness
Compliance Training and Education:
- Importance of continuous compliance training for employees
- Creating a culture of compliance and ethical behavior
- Role of awareness programs in preventing compliance breaches
Whistleblower Programs and Reporting Channels:
- Understanding the significance of whistleblower programs
- Designing effective reporting channels for internal reporting
- Protection and confidentiality measures for whistleblowers
Ethical Decision Making in Risk Management:
- Ethical considerations in risk management and compliance
- Applying ethical principles in decision-making processes
- Balancing business interests with ethical responsibilities
Evolving Regulatory Landscape and Future Trends:
- Staying updated with changes in regulatory requirements
- Anticipating future trends in compliance and risk management
- Implementing proactive measures for regulatory compliance

Capstone Project & Use Case

Project Overview
Complete projects to get experience and practice
Presentation of project findings and Insights
Industry Use Case Studies

Certification (Optional)

Certification Overview
Identify the right certification for you
Tips to prepare for certification

The post Business Competency (Fraud Analyst) – Bootcamp first appeared on Big Data Trunk.

]]> https://project.bigdatatrunk.com/courses/business-competency-fraud-analyst-bootcamp/feed/ 0