Azure Data Engineer With Gen AI

Course Overview

DP -900 AZURE DATA FUNDAMENTALS 

Syllabus - Week 1

• Explore core data concepts.
• Explore relational data on Azure.
• Explore non-relational data on Azure.
• Explore Analytics workload on Azure.
• DP 900 Certification.

Azure Data Factory

Syllabus - Week 2 - 4

• Master Data Pipelines & Data Flow using ADF.
• Handle variety of data source like: SQL server, Rest API, CSV/JSON , Parquet,ADLS.
• Incremental & batch pipeline.
• 4 Types of Trigger Implementation.
• Parameterization.
• Most Important: On-Prem to cloud Migration end to end.
• 10 Practical ADF Implementation.
• 10 Practical Assessment scenarios.
• Pipeline Monitoring Debugging and Performance Optimization.
• Real time project discussion and Master on ADF.

DP 203/DP 600/DP 700- Preparation

Syllabus - Week 5 -6

• Azure Data Factory
• Azure Synapse Analytics
• Azure Stream Analytics
• Azure Event Hubs
• Azure Data Lake Storage
• Azure Databricks
• Fabric

Python for Data Science/Engineering

• Syllabus - Week 6 - 7
• Introduction of Python
• Installing Python IDES – Python IDLE and Anaconda
• Writing Your First Python Program
• Data-types in Python
• Variables in Python – Declaration and Use
• Typecasting in Python
• Operators in Python – Assignment, Logical, Arithmetic etc.
• Taking User Input (Console)
• Conditional Statements – If else and Nested If else and elif
• Python Collections (Arrays) – List, Tuple, Sets and Dictionary
• Loops in Python – For Loop, While Loop & Nested Loops
• String Manipulation – Basic Operations, Slicing & Functions and Methods
• User Defined Functions – Defining, Calling, Types of Functions, Arguments
• Lambda Function
• Importing Modules – Math Module.

Syllabus - Object Oriented Programming in Python

• Basics of Object Oriented Programming
• Creating Class and Object
• Constructors in Python – Parameterized and Non-parameterized
• Inheritance in Python
• In built class methods and attributes
• Multi-Level and Multiple Inheritance
• Method Overriding and Data Abstraction
• Encapsulation and Polymorphism.

Advanced version of SOL

Syllabus - Week 8

• 1. Select
• 2. Distinct
• 3. IS NULL
• 4. WHERE
• 5. LIKE
• 6. Order by
• 7. Limit
• 8. Case
• 9. Rank and Dense Rank
• 10. Union and Union all
• 11. Exists
• 12. Count and its variant
• 13. Max, Min, Sum, Avg, etc
• 14. Round, Trunc, Substr
• 15. Alter, Update, Delete
• 16. Create, Insert
• 17. Listagg
• 18. Level/Connect By
• 1. And
• 2. Or
• 3. Greater Than
• 4. Less Than
• 1. Self join
• 2. Inner join
• 3. Cross join
• 4. Left and Right outer join
• 5. Full Outer Join
• 1. CTE expression
• 2. Independent and Correlated query
• 3. Different keys
• 4. Recursive CТЕ
• 5. Pivot
• 1. ROLL UP
• 2. Cumulative Sum
• 3. Lead
• 4. Lag
• 5. NTILE
• 6. ROW_NUMBER
• i) @LeetCode
• ii) @HackerRank

DSA(easy to medium)

Syllabus - Week 9

• ARRAYS
• STRINGS
• LINKED LIST
• STACK
• SORTING
• SEARCHING
• HASHING
• TREES
• QUEUE

Pyspark

Syllabus - Week 10

• Environment Setup
• Spark RDD
• spark Caching
• Common Transformations and Actions
• Spark Functions
• Key-Value Pairs
• Aggregate Functions
• Working with Aggregate Functions
• Joins in Spark
• Spark DataFrame
• Spark Shared Variables
• Custom Accumulator
• Spark and Fault Tolerance
• Broadcast variables
• Numeric RDD Operations
• Per-Partition Operations

Azure Data Bricks

Syllabus - Week 11-12

• Understand data and Spark Architectures
• Cluster Creation, Notebook Analysis
• Azure Databricks Workspace creation, delta tables, spark SQL, cluster
• management...
• RDDs / DataFrame /Spark SQL
• Data lake
• Delta lake
• Data Lakehouse architecture
• In depth spark performance optimization
• Partitioning bucketing caching, AQE and many more techniques
• Spark Streaming in Depth
• Databricks Project Implementation

Fabric Training Detailed

• Introduction to Microsoft Fabric
• Workspace Setup
• Data Lakehouse: Deep Understanding
• Data Ingestion and Data Processing Part 1
• Data Ingestion and Data Processing Part 2 with Spark
• Data Warehousing
• Data Pipeline and Stream Data
• End-to-End Project Part 1
• End-to-End Project Part 2

REAL TIME PROJECT

Syllabus - Week 13

• END TO END Project Implementation
• Fabric Project
• Gen -AI Project

INTERVIEW PREPARATION

Syllabus - Week 14 - 20

• Interview Questions Preparation
• Companies based interview
• technique Package negotiation secret
• skills Build Confidence Resume
• Preparation/ Linkedin

GEN -AI

• Introduction to Generative AI and Foundation Models (GPT, DALL·E, etc.)
• Key concepts: LLMs, Transformers, and use cases across industries
• Prompt Engineering: Techniques, best practices, and prompt types
• Exploring tools: ChatGPT, Bard, Claude, and Hugging Face
• Text generation, summarization, and Q&A with LLMs
• Image and code generation with Gen AI models
• Integration with Python and APIs (OpenAI, LangChain basics)
• Business use cases: content creation, chatbots, automation
• Responsible AI: bias, privacy, and ethical considerations
• Final mini project + roadmap to Gen AI career paths

Refund Policy

NON REFUNDLE

Quick Info

• Placement Guarantee: Yes
• Refundable: Yes
• Duration: 6 to 8 Month Days