AWS - Big Data Trunk

https://project.bigdatatrunk.com Quality Corporate and Classroom Training in Bay Area CA Sat, 07 Mar 2026 17:23:31 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 Build Your Own Private No-code RAG https://project.bigdatatrunk.com/courses/build-your-own-private-no-code-rag/ https://project.bigdatatrunk.com/courses/build-your-own-private-no-code-rag/#respond Thu, 05 Mar 2026 18:35:43 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=64634 Retrieval-Augmented Generation (RAG) has emerged as the industry standard for building AI systems that are both intelligent and secure—capable of delivering accurate, context-aware responses based exclusively on your organization’s private data.

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Build Your Own Private No-code RAG

Retrieval-Augmented Generation (RAG) has emerged as the industry standard for building AI systems that are both intelligent and secure—capable of delivering accurate, context-aware responses based exclusively on your organization’s private data.

Free E-learning Course

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Overview
Audience
Prerequisites
Curriculum

Description:

In this hands-on, half-day intensive workshop, participants will learn how to design and deploy a fully functional private AI chatbot without writing a single line of code. Using n8n, a powerful workflow automation platform, you will build a production-ready RAG system that connects your business documents (PDFs, Google Docs, websites, and more) to advanced language models from providers such as Gemini/OpenAI/Open-Source.

Rather than focusing on complex programming or theoretical concepts, this course emphasizes practical implementation. You will learn how to create embeddings, configure vector databases, implement retrieval pipelines, and deploy a secure chat interface that answers questions strictly from your curated knowledge base—protecting sensitive information while increasing operational efficiency.

By the end of the session, you will have built and tested your own private AI assistant tailored to a real-world business use case, ready for deployment to your website, internal teams, or customer support channel.

Duration:

Half Day

Course Code: BDT 538

Learning Objectives:

After this course, you will be able to:

Understand the 4-step RAG architecture
Configure AI nodes in n8n (LLMs, Memory, and Vector Stores)
Upsert private documents into a Vector Database without code
Deploy a functional chat interface that queries your private data
Implement basic "guardrails" to keep the bot on task

Business Analysts, Product Managers, Content Creators, and non-technical entrepreneurs who want to build custom AI solutions without writing code.

Basic understanding of AI concepts (LLMs) and ability to run n8n locally or via Docker. No coding experience required.

Course Outline:

Foundations of No-Code AI & RAG
1. What is RAG and why does your business need it?
2. Introduction to the n8n Canvas: Nodes, Triggers, and Actions
3. Lab: Connecting your first AI model (local or cloud based) to n8n

The "Brain" and the "Library": Embeddings & Vector Stores
1. How AI "reads" documents: Understanding Embeddings
2. Choosing a Vector Database: Explore different types of vector store (cloud based or local)
3. Lab: Building an automation that automatically "reads" and saves a PDF into the database

Building the Ingestion Pipeline
1. Document Loaders: How to pull data from PDFs, Google Drive, or Websites
2. The "Chunking" Strategy: Why size matters for AI accuracy
3. Lab: Building an automation that automatically "reads" and saves a PDF into the database

Creating the Chat Interface
1. Using the "AI Chat Agent": node in n8n
2. Connecting the Retriever: Linking the chat to your Vector Store
3. Adding "Memory": Ensuring the bot remembers the previous question
4. Lab: Testing your chatbot with "out-of-bounds" questions to ensure privacy

Advanced Tweaking & Deployment
1. System Prompts: Giving your bot a personality and specific rules
2. Exporting: your bot to a website
3. Lab: Final project—Customizing your bot for a specific use case (e.g., HR Assistant or Customer Support)

Training material provided: Yes (Digital format)

Hands-on Lab: Instructions will be provided to set up n8n and API keys.

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]]> https://project.bigdatatrunk.com/courses/build-your-own-private-no-code-rag/feed/ 0 Machine Learning with Snowflake: Snowpark & Cortex https://project.bigdatatrunk.com/courses/machine-learning-with-snowflake-snowpark-cortex/ https://project.bigdatatrunk.com/courses/machine-learning-with-snowflake-snowpark-cortex/#respond Mon, 03 Feb 2025 07:23:23 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=55377 The rapid evolution of artificial intelligence (AI) and machine learning (ML) is transforming industries worldwide.

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Overview
Prerequisites
Audience
Curriculum

Description:

The rapid evolution of artificial intelligence (AI) and machine learning (ML) is transforming industries worldwide. From personalized customer experiences to real-time fraud detection, organizations are leveraging ML to drive innovation and gain a competitive edge. Snowflake, with its powerful data platform, has emerged as a leader in enabling end-to-end ML pipelines, empowering data professionals to harness the full potential of their data.

This course equips students with the skills to navigate this transformative landscape, combining the scalability of Snowflake with advanced ML capabilities through Snowpark and Cortex. Over three days, students will learn how to build ML workflows that are seamless, scalable, and optimized for modern data engineering and analytics. With Snowflake's recent advancements in Large Language Model (LLM) integration and in-database ML, participants will gain firsthand experience with cutting-edge technologies shaping the future of AI.

Whether you're a data scientist, ML engineer, or analytics professional, this course will help you stay ahead of industry trends and enable you to deploy powerful, real-time ML models in Snowflake's unified platform.

Duration: 3 Day

Course Code: BDT396

Learning Objectives:

After this course, students will be able to:

Understand Snowflake’s architecture for machine learning pipelines and integration with external datasets
Develop ML pipelines using Snowpark for scalable data preparation and modeling
Utilize Cortex for advanced ML pipeline development, including model training and deployment
Implement and execute ML functions and LLM functions in Cortex for real-world use cases
Optimize end-to-end ML workflows using Snowflake’s capabilities

Familiarity with programming language – especially Python
Basics of using Snowflake and SQL
Prior knowledge of Machine Learning will be useful but not required

This course is designed for Software Developers, Data Scientists, Software Architects, Quality Assurance Engineers, Data Analysts to build and implement generative AI models. Familiarity with machine learning concepts (like neural networks) is helpful but not required.

Course Outline:

Snowflake Overview
1. Quick review of Snowflake Architecture
2. Understanding data ingestion from external sources
3. Demos and Labs
Machine Learning Overview
1. Understand the concept of machine learning
2. Learn about data wrangling & preparing data for machine learning
3. Understanding machine learning techniques: Classification & Regression
4. Learn about metrics for validating these techniques
5. Working with hyper parameters, cross validation
6. Build machine learning pipelines
7. Multiple Demos and Labs
Machine Learning pipelines with Snowpark
1. What are Snowpark components?
2. Snowflake Python connector vs Snowpark – what is the difference?
3. Working with UDF, Vectorized UDF, Functions, Procedures
4. Pandas vs Snowpark Dataframes
5. ML Pipelines with Snowpark
6. Multiple Demos and Labs
Machine Learning pipelines with Snowpark ML (Cortex)
1. Introduction to Snowpark ML APIs
2. Data Collections with Filesystem and FileSet
3. Distributed pipelines with Snowpark ML
4. Hyper parameter tuning with Snowpark ML
5. Model predictions with registered models
6. Multiple Demos and Labs
Machine Learning Functions with Cortex
1. What are machine learning functions in cortex
2. Performing Time-series forecasting, anomaly detection, classification with ML Functions
3. Using Snowflake SQL classes and instances
4. Building Classification and Regression Models with Spark machine learning library
5. Understanding the costs involved in using Machine Learning Functions
6. Multiple Demos and Labs
LLM (Large Language Model) Functions with Cortex
1. Understand support for various LLM models on Snowflake
2. Integrate with ChatGPT models
3. Using LLM functions: COMPLETE, SENTIMENT, SUMMARIZE, TRANSLATE, etc
4. Understanding the costs involved in using these LLMs
5. Multiple Demos and Labs

Training material provided: Yes (Digital format)

Hands-on Lab: Students will create a trial Snowflake account for the hands-on labs. If required virtual machines will be provided

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]]> https://project.bigdatatrunk.com/courses/machine-learning-with-snowflake-snowpark-cortex/feed/ 0 Data Engineering and Analytics on AWS (Amazon Web Services) https://project.bigdatatrunk.com/courses/data-engineering-and-analytics-on-aws-amazon-web-services/ https://project.bigdatatrunk.com/courses/data-engineering-and-analytics-on-aws-amazon-web-services/#respond Tue, 26 Nov 2024 13:19:40 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=54793 This training provides a hands-on introduction to data engineering and analytics capabilities on AWS. Participants will learn how to build scalable data pipelines, process and analyze data, and use key AWS services such as AWS Glue, Redshift, and Athena.

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Overview
Prerequisites
Audience
Curriculum

Description:

This training provides a hands-on introduction to data engineering and analytics capabilities on AWS. Participants will learn how to build scalable data pipelines, process and analyze data, and use key AWS services such as AWS Glue, Redshift, and Athena. The training emphasizes practical applications of AWS tools to manage and analyze large datasets efficiently. By the end of the session, attendees will have the foundational skills to design and implement data workflows and analytics solutions on AWS.

Duration: 1 Day

Course Code: BDT33

Learning Objectives:

By the end of this training, participants will be able to:

Identify the key data engineering and analytics services on AWS.
Build data pipelines using AWS Glue and S3.
Analyze large datasets using Redshift and Athena.
Integrate real-time and batch processing workflows.
Evaluate AWS-based solutions for analytics in business scenarios.

Basic knowledge of cloud computing and data concepts is recommended. Familiarity with SQL is beneficial but not mandatory.

Data engineers and analysts exploring AWS for data solutions.
IT professionals seeking to implement data pipelines and analytics workflows.
Business managers interested in AWS-based analytics solutions.

Course Outline:

Module 1: Introduction to AWS Data Engineering and Analytics

Overview of Data Engineering and Analytics Concepts
AWS Data Ecosystem: S3, Glue, Redshift, Athena, Kinesis

Module 2: Data Storage and ETL Pipelines with AWS Glue

Introduction to AWS Glue for Data Integration
Building ETL Pipelines and Cataloging Data
Hands-On: Creating an ETL Workflow

Module 3: Analytics with Redshift and Athena

Overview of Amazon Redshift for Data Warehousing
Serverless Analytics with Amazon Athena
Hands-On: Querying and Analyzing Data

Module 4: Real-Time Data Processing with Amazon Kinesis

Introduction to Streaming Data Processing
Designing Real-Time Workflows with Kinesis Data Streams

Module 5: Real-World Use Cases and Best Practices

Applications of Data Engineering on AWS
Best Practices for Scalability and Cost Optimization
Q&A and Additional Resources

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/data-engineering-and-analytics-on-aws-amazon-web-services/feed/ 0 Big Data on Amazon Web Services https://project.bigdatatrunk.com/courses/big-data-on-amazon-web-services/ https://project.bigdatatrunk.com/courses/big-data-on-amazon-web-services/#respond Tue, 26 Nov 2024 12:59:41 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=54783 This training is designed to provide a comprehensive understanding of Big Data solutions on Amazon Web Services (AWS). Over three days, participants will explore how AWS enables scalable and secure data processing, storage, and analytics. The training covers essential services such as Amazon S3, EMR, Redshift, and Kinesis, while emphasizing best practices in managing large datasets.

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Overview
Prerequisites
Audience
Curriculum

Description:

This training is designed to provide a comprehensive understanding of Big Data solutions on Amazon Web Services (AWS). Over three days, participants will explore how AWS enables scalable and secure data processing, storage, and analytics. The training covers essential services such as Amazon S3, EMR, Redshift, and Kinesis, while emphasizing best practices in managing large datasets. Attendees will gain hands-on experience with designing and implementing Big Data workflows and learn how to harness AWS tools to drive insights and business value from data.

Duration: 3 Days

Course Code: BDT28

Learning Objectives:

By the end of this training, participants will be able to:

Describe the key components of Big Data solutions on AWS.
Implement scalable storage and processing of large datasets using AWS services.
Analyze data using AWS analytics tools such as Redshift and QuickSight.
Design Big Data workflows to handle real-world business challenges.
Optimize performance and cost for Big Data workloads on AWS.

Participants should have basic knowledge of cloud computing and familiarity with fundamental data concepts such as storage, databases, and analytics.

Data professionals looking to leverage AWS for Big Data solutions.
Cloud architects and engineers exploring AWS Big Data services.
Developers and analysts seeking to build scalable analytics pipelines.

Course Outline:

Day 1: Foundations of Big Data and AWS Services

Module 1: Introduction to Big Data

What is Big Data? Characteristics and Challenges
The Role of Cloud in Big Data

Module 2: AWS Big Data Ecosystem

Overview of Key Services: S3, EMR, Redshift, Kinesis, and Athena

Big Data Architecture on AWS

Module 3: Storage and Data Ingestion

Data Storage: Deep Dive into Amazon S3
Ingestion Services: AWS Glue, Kinesis, and Data Pipelines
Hands-On: Setting Up Data Ingestion

Day 2: Data Processing and Analysis

Module 4: Processing Big Data on AWS

Amazon EMR for Data Processing
Introduction to Apache Spark and Hadoop on AWS
Hands-On: Running a Data Processing Job on EMR

Module 5: Data Warehousing with Redshift

Setting Up and Managing Redshift Clusters

Optimizing Redshift for Query Performance
Hands-On: Querying Data with Redshift

Module 6: Data Visualization and Analysis

Using Amazon QuickSight for Business Intelligence
Hands-On: Creating Dashboards

Day 3: Advanced Topics and Best Practices

Module 7: Streaming Data Processing

Real-Time Analytics with Amazon Kinesis
Hands-On: Building a Real-Time Data Pipeline

Module 8: Security and Governance

Best Practices for Data Security on AWS
Compliance and Data Governance

Module 9: Cost Management and Optimization

Cost-Effective Strategies for Big Data Workloads
Using AWS Cost Management Tools

Module 10: Capstone Project

End-to-End Workflow: Ingest, Process, Store, and Analyze Data

Presenting Findings and Solutions

Module 11: Review and Wrap-Up

Key Takeaways and Resources for Further Learning
Q&A Session

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/big-data-on-amazon-web-services/feed/ 0 AWS DynamoDB with JavaScript https://project.bigdatatrunk.com/courses/aws-dynamodb-with-javascript/ https://project.bigdatatrunk.com/courses/aws-dynamodb-with-javascript/#respond Wed, 20 Nov 2024 13:14:40 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=54545 This course provides a comprehensive introduction to Amazon DynamoDB, covering how to design, create, and interact with DynamoDB databases using JavaScript.

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Overview
Prerequisites
Audience
Curriculum

Description:

This course provides a comprehensive introduction to Amazon DynamoDB, covering how to design, create, and interact with DynamoDB databases using JavaScript. Topics include data modeling, querying, and best practices in performance optimization for DynamoDB. Participants will gain hands-on experience with DynamoDB’s key features using the AWS SDK for JavaScript.

Duration: 3 Days

Course Code: BDT384

Learning Objectives:

After completing this course, participants will be able to:

Understand the fundamentals of DynamoDB and its NoSQL architecture
Design and implement data models in DynamoDB
Use the AWS SDK for JavaScript to interact with DynamoDB
Perform CRUD operations, querying, and scanning in DynamoDB
Optimize DynamoDB performance for cost-effective applications
Implement DynamoDB streams, triggers, and backup strategies

Basic knowledge of JavaScript
Familiarity with cloud concepts and basic AWS services

Web developers, software engineers, and data engineers looking to integrate Amazon DynamoDB with JavaScript applications for fast, scalable, and serverless data storage solutions.

Course Outline:

Module 1: Introduction to AWS DynamoDB

Topics Covered:

Overview of DynamoDB: Key Features and Use Cases
DynamoDB vs. Relational Databases (SQL)
Core Concepts: Tables, Items, Attributes
Primary Keys: Partition Keys and Sort Keys
DynamoDB Data Types
Provisioned vs. On-Demand Capacity Modes

Hands-On Labs:

Setting up an AWS DynamoDB environment
Creating a DynamoDB table using the AWS Management Console

Module 2: Getting Started with AWS SDK for JavaScript

Topics Covered:

Setting Up the AWS SDK for JavaScript
Configuring AWS Credentials
Introduction to DynamoDB SDK Methods
Working with DocumentClient vs. DynamoDB Client

Hands-On Labs:

Initializing AWS SDK and setting up JavaScript project
Using DocumentClient to interact with DynamoDB tables

Module 3: CRUD Operations in DynamoDB with JavaScript

Topics Covered:

Creating Items with put Operation
Reading Items with get Operation
Updating Items with update Operation
Deleting Items with delete Operation
Batch Operations: BatchGetItem and BatchWriteItem

Hands-On Labs:

Adding and reading data in DynamoDB with JavaScript
Performing batch operations for efficient data processing

Module 4: Querying and Scanning Data

Topics Covered:

Queries vs. Scans in DynamoDB
Querying by Partition Key and Sort Key
Using Filters, Expressions, and Conditions in Queries
Pagination and Handling Large Datasets
Best Practices for Query and Scan Performance

Hands-On Labs:

Querying data with filters and expressions
Implementing pagination for large dataset handling

Module 5: Data Modeling in DynamoDB

Topics Covered:

Designing for NoSQL and DynamoDB: Data Modeling Basics
Single Table Design vs. Multiple Table Design
Secondary Indexes: Global and Local Secondary Indexes
Normalization vs. Denormalization
Optimizing Data Models for Read and Write Efficiency

Hands-On Labs:

Creating Global and Local Secondary Indexes
Implementing single-table design with multiple entities

Module 6: DynamoDB Performance Optimization

Topics Covered:

Understanding DynamoDB Capacity Units (Read/Write)
Strategies for Reducing Read and Write Costs
Fine-Tuning with Provisioned Capacity and Auto-Scaling
Implementing Caching with DynamoDB Accelerator (DAX)

Hands-On Labs:

Configuring auto-scaling for DynamoDB tables
Setting up and using DynamoDB Accelerator (DAX) for caching

Module 7: DynamoDB Streams and Triggers

Topics Covered:

Introduction to DynamoDB Streams and Event-Driven Architecture
Setting up Lambda Triggers with DynamoDB Streams
Real-time Data Processing with DynamoDB Streams and Lambda
Event Sourcing and Change Data Capture (CDC)

Hands-On Labs:

Configuring a Lambda function trigger for DynamoDB Streams
Processing real-time changes with a DynamoDB stream

Module 8: Backup, Restore, and Security

Topics Covered:

DynamoDB Backup and Restore Options
Point-in-Time Recovery (PITR)
Access Control with IAM Roles and Policies
Encryption at Rest and in Transit

Hands-On Labs:

Setting up automatic backups for DynamoDB tables
Configuring IAM roles and policies for table access control

Structured Labs and Project

Structured Labs:

Lab: Creating a DynamoDB table with primary and secondary indexes
Lab: Performing CRUD operations using AWS SDK for JavaScript
Lab: Designing a single-table architecture with multiple entities
Lab: Setting up DynamoDB Streams with Lambda triggers
Lab: Configuring DAX for performance optimization
Lab: Implementing backup and recovery solutions

Final Project:

Project: Build a JavaScript application that interacts with a DynamoDB database, implementing features such as data storage, querying, and real-time updates using streams and Lambda.

Training material provided: Yes (Digital format)

Additional Information

Any additional information about Labs / Software Installs required for the course

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]]> https://project.bigdatatrunk.com/courses/aws-dynamodb-with-javascript/feed/ 0 Byte-Sized Devops Series: Introduction To Cloud Infrastructure Automation With AWS Cloud Formation https://project.bigdatatrunk.com/courses/byte-sized-devops-series-introduction-to-cloud-infrastructure-automation-with-aws-cloud-formation/ https://project.bigdatatrunk.com/courses/byte-sized-devops-series-introduction-to-cloud-infrastructure-automation-with-aws-cloud-formation/#respond Sat, 20 May 2023 08:22:49 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=29576 A short session intended to provide an overview of building cloud infrastructure as code with AWS Cloud Formation.

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Overview
Prerequisites
Audience
Curriculum

Session Description:

Join our Byte-Sized DevOps Series for a concise introduction to the world of cloud infrastructure as code with AWS CloudFormation. In this brief yet informative session, we'll provide an overview of the fundamentals, empowering you to efficiently build and manage your cloud infrastructure. Elevate your skills in rapid delivery and harness the power of AWS CloudFormation. Get ready to streamline your cloud operations and embark on a journey towards efficient infrastructure management with Byte-Sized DevOps Series

Course Code/Duration:

BDT79 / 90 Minutes

Learning Objectives:

Learn about Cloudformation basics, comparison with other similar tools, and we will then perform hands-on lab to do the following:

Gain a foundational understanding of cloud infrastructure as code.
Learn the fundamentals of AWS Cloud Formation for efficient cloud infrastructure management.
Enhance skills in rapid delivery and automation of cloud resources.
Streamline cloud operations by leveraging AWS Cloud Formation's capabilities.
Prepare to efficiently manage and optimize cloud infrastructure using the Byte-Sized DevOps Series.

Having some basic idea of what it takes to create cloud infrastructure manually in AWS, helps you appreciate how Cloudformation enables smoother operations, better change management and faster deployments.

This session is designed for developers, operations or devops members who have some basic idea of cloud computing. Are interested to know how to automate cloud infrastructure such as creation of virtual machines, load balancers, databases, firewalls etc. by just using a bunch of configuration files.

Course Outline:

Introducing AWS CloudFormation
Exploring the Fundamentals of CloudFormation
Crafting CloudFormation Scripts
Running and Implementing CloudFormation Templates

Training Material Provided: Yes (Digital Format)

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]]> https://project.bigdatatrunk.com/courses/byte-sized-devops-series-introduction-to-cloud-infrastructure-automation-with-aws-cloud-formation/feed/ 0 Cloud for Non-Programmers https://project.bigdatatrunk.com/courses/cloud-for-non-programmers/ https://project.bigdatatrunk.com/courses/cloud-for-non-programmers/#respond Mon, 01 May 2023 00:24:35 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=26814 This course will guide you about cloud computing technology and describe its impact on IT scenario. In this course, you’ll learn about core Cloud business drivers,

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Overview
Prerequisites
Audience
Curriculum

Description:

This course will guide you about cloud computing technology and describe its impact on IT scenario. In this course, you’ll learn about core Cloud business drivers, how to determine whether business transformation is right for your team, and how to build short- and long-term projects with the power of the cloud. You would be exposed to several cloud services and how to compare them for use cases.

Duration: Half Day

Course Code: BDT272

Learning Objectives:

After this course, you will be able to:

Understand the benefits of Cloud Computing
Compare Cloud Providers
Exposure to the various services offered by Cloud Providers

To ensure success in this course, basic knowledge of working with computers and familiarization with the core functioning of an organization is highly recommended.

This course is designed for:

Those with little to no experience with Cloud
Business user and others interested in Cloud

Course Outline:

Module 1: Understanding the value of Cloud

The economy of cloud computing/terminology
Pros and Cons of moving to the Cloud

Module 2: Introduction to Cloud Computing

Cloud Computing—An Overview
Cloud Components
Comparison of Cloud platforms
Is it possible to have hybrid environment vs. all in the cloud?
Walkthrough: Success stories

Module 3: Differentiating Cloud Services

Infrastructure as a Service (IaaS) – An Overview
Platform as a Service (PaaS) – An Overview
Software as a Service (SaaS) – An Overview
Walkthrough: Cloud Computing use case

Module 4: Cloud Pillars

Scale – Agility and Speed
Capability – Range of services
Operational excellence – High availability
Security – privacy, availability, security, and compliance.
Cost optimization
Quizzes

Module 5: Cloud Offerings

Understand various Cloud Services
Explain the key characteristics of Cloud like On-demand service, horizontal scalability, pay as you go etc.
Understand pricing models on cloud

Module 6: Cloud Services

Cloud service overview
Core Cloud Services
Pricing
How to decide on which computer option is right for you?

Module 7: Reference Material and next steps

Reference Material and next steps

Training material provided: Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/cloud-for-non-programmers/feed/ 0 Kickstart Terraform with AWS in a Day https://project.bigdatatrunk.com/courses/kickstart-terraform-with-aws-in-a-day/ https://project.bigdatatrunk.com/courses/kickstart-terraform-with-aws-in-a-day/#respond Tue, 04 Oct 2022 10:50:18 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=25224 Cloud technologies are everywhere these days, and demand for people able to work with these technologies is growing every day. Terraform, an open-source Infrastructure as Code (IaC) tool that is effective and efficient in managing cloud resources. It allows you to build, change and version infrastructure efficiently and safely.

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Overview
Prerequisites
Audience
Curriculum

Description:

Cloud technologies are everywhere these days, and demand for people able to work with these technologies is growing every day. Terraform, an open-source Infrastructure as Code (IaC) tool that is effective and efficient in managing cloud resources. It allows you to build, change and version infrastructure efficiently and safely. In this course you will learn about using the Hashicorp language syntax and how to use it to configure and manage cloud resources. You will also understand about how terraform manages and maintain resource states. All the hands-on labs will be geared towards AWS, and the students are expected to create a “free AWS” account.

Course Code/Duration:

BDT256 / 1 – Day

Learning Objectives:

Upon completing this course, you will:

Master Terraform and Cloud Fundamentals.
Expertly use HashiCorp configuration language.
Efficiently manage Terraform states.
Utilize Terraform modules for streamlined infrastructure management.
Build professional AWS cloud infrastructure with Terraform.

Basic knowledge Linux and AWS

This course is designed for anyone interested to get started with using terraform. It is geared towards DevOps engineers, Cloud engineers, Cloud Solution Architects, System engineers, Infrastructure engineers.

Course Outline:

Terraform and Cloud Fundamentals

What is terraform?
AWS basics: VPC, EC2, Regions and Zones
Terraform basic commands
Hands-on: Creating an IAM user

Hashicorp configuration language (HCL)

Terraform data types: Numbers, strings, bools, collections
Terraform count and for_each
Dynamic blocks
Conditional expressions
Built-in functions
Hands-on lab with these topics

Terraform states

Backends and remote state management
Remote state on Amazon S3
Managing secrets with Terraform
Storing secrets in AWS secrets manager
Hands-on labs with these topics

Terraform modules

Introduction to terraform modules
Refactoring modules and access output values
Introduction to Terraform registry
Exploring VPC, Security Group and EC2 module
Hands-on lab with ANN for Classification

Building professional AWS infrastructure with Terraform

Terraform providers
Configuration Syntax
Terraform plan and apply
Formatting and validating configuration files
Terraform data sources
Hands-on lab with building different AWS resources

Training material provided: Yes (Digital format)

Hands-on Lab:
Instructions will be provided to install Terraform on Linux, macOS and Windows.
It is advised that the students create a free AWS account so that they can do hands-on labs.

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]]> https://project.bigdatatrunk.com/courses/kickstart-terraform-with-aws-in-a-day/feed/ 0 Amazon Web Services (AWS) https://project.bigdatatrunk.com/courses/amazon-web-services-aws/ https://project.bigdatatrunk.com/courses/amazon-web-services-aws/#respond Wed, 16 Mar 2022 01:31:59 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=23804 Cloud computing is dominated by two major players: Amazon Web Services (AWS) and Azure.

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Overview
Prerequisites
Audience
Curriculum

Description:

Unlock lucrative career opportunities in the thriving world of cloud computing with Amazon Web Services (AWS) training. As the global leader in cloud services, AWS commands an impressive 47.1 percent market share, making AWS Solutions Architect roles highly promising and well-compensated. Whether you're a beginner looking to enter the cloud domain or an intermediate developer with years of experience, learning AWS is your gateway to salary growth and career advancement. Embrace AWS certification to acquire essential skills and stay ahead in the competitive cloud industry. Elevate your career prospects and join the AWS ecosystem today!

Course Code/Duration:

BDT192 / 5 Days

Learning Objectives:

After this course, you will be able to:

Introduction to is Cloud Computing.
Benefit of Cloud Computing.
AWS Platform
EC2 – Introduction and Fundamental
EC2 – Security Group, SSH overview, Instance connect, Run time script
EC2 – Instance Storage
Introduction and implementation of High Availability & Scalability
What is RDS, Aurora and Elastic Cache
AWS S3 – Life Cycle, Bucket & Object, CORS
CloudFront and Global Accelerator
How to achieve decoupling using SQS, SNS, Kinesis
What is Serverless Architecture and achieve it.
Different Database in AWS – RDS, Redshift, Athena
How to do AWS Monitoring
Virtual Private Cloud

Just keen for learning cloud concept and hands on.

Anyone want to learn cloud concept using AWS Hands on.

Course Outline:

1. Introduction – AWS & Getting started

AWS Cloud Overview
Create account id.
PaaS, SaaS, IaaS
All basic Services

2. EC2 Fundamentals

EC2 Basic
Create an EC2 Instance and Test
Security Groups
SSH Ovierview
EC2 Instance Connect
Run initial script for EC2 Testing
Different type of EC2.
EC2 Placement Group

3. EC2 Instance Storage

EBS Overview
EBS Hands On
EBS Snapshots Hands On
AMI
EBS Encryption
EFS vs EBS

4. High Availability and Scalability

Intro of ASB
High Availability and Scalability
Load Balancer – Intro, Uses and Hand on
- Classic Load Balancer
- Network Load Balancer
- Application Load Balancer
Auto Scaling Groups (ASG) Overview
ASG – Hands On

5. RDS, Aurora and Elastic Cache

RDS Overview
RDS Hands On
Aurora Overview and Hands On
Elastic Search Overview

6. Amazon S3

Basic of S3
S3 Life Cycle
Buckets and Object
S3 Encryption and Versioning – Hands On
Bucket Policy
CORS
Identity Operators
Operators Precedence

7. CloudFront and AWS Global Accelerator

CloudFront Overview and Architecture
CloudFront with S3 – Hands On
AWS Global Accelerator
AWS Global Accelerator – Hands On

8. Decoupling – SQS, SNS, Kinesis, Active MS

Introduction to Messaging
SQS – Basic Explanation
SQS – Hands On
SQS – Dead Letter Queue
SQS – Delay Queues
Fan Out – SNS and SQS

9. Serverless Architecture

Intro
Lambda Overview and Hands On
DynamoDB Overview and Hands On
API Gateway Overview
API Gateway Hands on

10. Databases in AWS

RDS
AURORA
ElasticSearch
Redshift
Athena
Glue

11. AWS Monitoring

CloudWatch Metrics
CloudWatch Metrics and Dashboard
CloudWatch Alarms
CloudWatch – Hands On
CloudTrail Intro and Hands On
CloudTrails vs CloudWatch vs Config

12. Virtual Private Cloud – VPC

VPN – Introduction
Subset and Bastion Hosts Infro
Complete setup of VPN – Hands On
NAT instance – Hands on
VPC peering
VPC Endpoint

Doubt Clearing / Queries session

Training material provided:

Yes (Digital format)

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]]> https://project.bigdatatrunk.com/courses/amazon-web-services-aws/feed/ 0 Networking in Amazon Web Services https://project.bigdatatrunk.com/courses/networking-in-amazon-web-services/ https://project.bigdatatrunk.com/courses/networking-in-amazon-web-services/#respond Mon, 14 Feb 2022 05:11:26 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=23527 Everyday cloud computing is gaining more and more traction as number of organizations – large and small are starting to adopt it. Amazon Web Services (AWS)

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Overview
Prerequisites
Audience
Curriculum

Description:

Everyday cloud computing is gaining more and more traction as number of organizations – large and small are starting to adopt it. Amazon Web Services (AWS) is a leader in this space. Organizations are either migrating to AWS or are adopting a hybrid deployment for their computing needs. At the heart of any cloud computing deployment is networking.
Cloud networking requires understanding of various topics such as Virtual Private Cloud (VPCs), Load Balancers, Network Security, DNS services, etc. This course will explain these concepts and provide hands-on experience on AWS.

Course Code/Duration:

BDT117 / 1 Day

You must understand AWS concepts (terms such as EC2, S3, etc.).
Also, should understand routing and IP addresses.

This session is designed for software developers, software architects, network engineers, system operators managing cloud.

Course Outline:

Understand Virtual Private Cloud (VPC)
- Exploring default VPC and VPC with private subnet
- Limits of VPC in a private subnet
- Routing and Subnets with in VPC
- Lab: Implementing and troubleshooting an IPv4 network
Using ENIs, EIPs, Bastion Hosts
- Assigning Elastic IP (EIP), Elastic Network Interface (ENI) and associating them to EC2
- Using Bastion hosts
Using Placement Groups for network performance improvements
Network Address Translation in AWS VPC
- NAT on EC2 within a VPC
- Using NAT gateways
- NAT gateway rules and limitations
VPC peering
- Overview of VPC peering
- Overlapping CIDR Ranges
Understand VPC security
- Security Groups in AWS
- Network ACLs
- Using Virtual Private Gateway (VPW) in VPC
Elastic load balancers and their usage
- Introduction to Elastic Load Balancers (ELB)
- Understanding Listeners and Target Groups
Using DNS on AWS
- Introduction to Route 53
- Private hosted DNS zones with AWS Route 53
Hybrid deployments
- Understanding Hybrid deployments
- Using VPN to connect On-Premises resource with AWS
- Direct connection to AWS from On-Premises using virtual interfaces
Managing costs related to networking
- Transfer charges within AWS accounts
- VPC pricing

Lab Environment

We will be using Qwiklabs that will give us step by step instructions to perform various networking tasks on the AWS platform.

Training material provided:

Yes (Digital format)

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