1 PySpark Introduction 1.0h

1 SparkSession & Creating DataFrames

2 PySpark Introduction & Spark Architecture

3 Reading & Writing Files

4 Column Operations

5 Row Operations & Filtering

6 Data Cleaning & Null Handling

7 Built-in Functions & Expressions

8 String & Date Functions

9 Aggregation & GroupBy

10 Joins & Union

11 Window Functions

12 User Defined Functions (UDFs)

13 Spark SQL

14 Performance Optimization

15 Partitioning & File Management

16 PySpark Performance Tuning

17 Spark Streaming (Structured Streaming)

18 Delta Lake & Lakehouse

19 End-to-End ETL Project

20 PySpark Interview Questions

21 PySpark Coding Challenges

1 Database Introduction 1.0h

1 SQL Introduction & Database Fundamentals

2 SELECT Statement & Basic Queries

3 Filtering, Sorting & Limiting Data

4 SQL Functions

5 Aggregate Functions & GROUP BY

6 HAVING Clause & Advanced Aggregations

7 Joins

8 Set Operators

9 Subqueries

10 Common Table Expressions (CTEs)

11 Window Functions

12 CASE Statement & Conditional Logic

13 DML Operations

14 DDL & Constraints

15 Views, Indexes & Performance

16 Stored Procedures & Functions

17 Transactions & ACID

18 Advanced SQL Scenarios

19 SQL for Data Engineering

20 Real-Time SQL Capstone Project

21 SQL Interview Questions

1 AWS Cloud Provider introduction 1.0h

1 AWS Core Services 1.0h

1 AWS IAM

2 Amazon S3

3 Amazon EC2

4 Amazon VPC

5 AWS Lambda

6 Amazon API Gateway

7 Amazon SQS

8 Amazon SNS

9 Amazon EventBridge

10 AWS Glue

11 AWS Step Functions

12 Amazon CloudWatch

13 AWS Secrets Manager

14 AWS KMS

15 Amazon Athena

16 Amazon EMR

17 Amazon Kinesis Introduction & Streaming Concepts

18 Amazon MSK (Apache Kafka) Complete Course

1 AWS Lambda ETL 1.0h

1 Project: Hello World Lambda

2 S3 File Processing

3 API Development using Lambda

4 Serverless CRUD API

5 Image Processing Pipeline

6 Event-Driven Notification System

7 Asynchronous Processing

9 Secrets Manager Integration

10 Data Warehouse Loader

1 AWS Glue ETL 1.0h

1 Project 1 : First AWS Glue Job

2 Project 2 : CSV to Parquet Converter

3 Project 3 : Data Cleaning Pipeline

4 Project 4 : Glue Crawler & Data Catalog

5 Project 5 : Partitioned ETL Pipeline

6 Project 6 : Incremental ETL using Job Bookmarks

7 Project 7 : Multi-Source Data Integration

8 Project 8 : SCD Type 1 & Type 2

9 Project 9 : Error Handling & Logging Framework

10 Project 10 : Glue Workflow Automation

1 AWS EMR ETL Introduction 1.0h

1 Project 1 : First EMR Cluster & Spark Job

2 Project 2 : Large CSV Processing

3 Project 3 : Hive Data Warehouse

4 Project 4 : Partitioned ETL Pipeline

5 Project 5 : Multi-Source Data Integration

6 Project 6 : Incremental ETL Pipeline

7 Project 7 : Spark Performance Optimization

10 Project 10 : Real-Time Log Processing

1 Databricks Introduction 1.0h

1 Databricks Introduction & Lakehouse Architecture

2 Databricks Workspace & Compute Clusters

3 Unity Catalog & Data Governance

4 Databricks Notebooks & Development Environment

5 DBFS, Volumes & Data Ingestion

6 Delta Lake Fundamentals

7 Delta Lake Advanced Operations

8 Spark SQL in Databricks

9 PySpark ETL in Databricks

10 Auto Loader (cloudFiles)

11 Delta Live Tables (Lakeflow Declarative Pipelines)

12 Databricks Workflows & Job Scheduling

13 Structured Streaming

14 CI/CD using Databricks Asset Bundles (DAB)

15 Git Integration & Databricks Repos

16 End-to-End Production Lakehouse Project

17 Databricks Interview Questions

1 AI Prompt Engineering Introduction 1.0h

1 Devops Introduction 1.0h

1 Batch and Streaming Process Introduction 1.0h

1 Design Patterns Introduction 1.0h

1 Python Introduction 1.0h

2 Python Data types 0.3h

3 Data Operators 0.3h

4 Python functions 0.3h

5 Python OOPs Concept Introduction 0.3h

6 Python Class Introduction 1.0h

7 Python Inheritance Concept 1.0h

8 Python Abstract Class 1.0h

9 Python General Topics 1.0h

10 Python Interview Questions Part-1 1.0h

11 Python Interview Questions Part-2 1.0h

1 Pandas Introduction 1.0h

2 Pandas Introduction & DataFrame Basics 1.0h

3 Reading & Writing Files

4 Column Operations

5 Row Operations & Indexing

6 Data Cleaning

7 Filtering & Conditional Selection

8 String Operations

9 Date & Time Operations

10 Aggregation & GroupBy

11 Joins, Merge & Concatenate

12 Sorting, Ranking & Window Functions

13 Statistics & Apply Functions

14 Real-Time ETL Project

15 Interview Questions & Coding Problems

1 Amazon Redshift Introduction & Architecture

2 Redshift Cluster Setup & Database Objects

3 Data Loading into Redshift

4 SQL in Amazon Redshift

5 Data Distribution Styles

6 Sort Keys & Table Design

7 Compression Encoding

8 Query Performance Optimization

9 Workload Management (WLM)

10 Redshift Spectrum

11 Security & Access Management

13 Monitoring & Troubleshooting

14 Redshift Integration with AWS Services

15 Real-Time Data Loading

18 End-to-End Redshift Project

19 Amazon Redshift Interview Questions

1 DynamoDB Introduction & Core Concepts

2 Creating Tables & Data Modeling

3 CRUD Operations

4 Querying & Indexing

5 Advanced Data Modeling

6 Performance & Scaling

7 Streams & Event-Driven Architecture

9 DynamoDB with AWS Lambda & ETL

10 Real-Time Project & Interview Questions

1 Redis Introduction & Architecture

2 Redis Data Types & CRUD Operations

3 Expiration, TTL & Caching

4 Advanced Data Structures & Pub/Sub

6 Redis with Python & AWS

8 Redis for AWS Data Engineers

9 Real-Time Project & Interview Questions