Data Engineering with AI
Data Engineering with AI (Python + SQL + Real-Time Projects)
Learn Data Engineering + AI — Step into One of the Highest Paying IT Careers.
- Duration: 3–4 Months
- Mode: Online
- Placement Support: Yes
Build Future-Ready Data Engineering Skills With AI
Step into the world of modern Data Engineering with AI integration. This course is designed to help you become a job-ready data engineer by combining strong fundamentals with real-world project experience.
Learn how to design, build, and manage data pipelines, ETL workflows, and scalable data systems using modern tools and AI-powered techniques like ChatGPT and Copilot.
You will gain hands-on experience working with Python, SQL, data warehousing, and cloud technologies, while learning how to process and transform large-scale data efficiently.
Through real-world scenarios and projects, you’ll develop the confidence to work in production-level data environments.
What You Will Learn
SQL for data analysis & querying
Python for data processing (Pandas, NumPy)
ETL & Data Pipeline Development
Data Warehousing Concepts
Big Data Basics (Spark Introduction)
AI-powered data engineering workflows
Who Should Enroll?
- Freshers (any background)
- Non-IT candidates
- Testers/Developers switching to Data Engineering
- Anyone interested in data careers
Outcome
After completing this course, you will be able to:
- Build data pipelines from scratch
- Work with real-world datasets
- Automate data workflows
- Understand end-to-end data architecture
- Crack Data Engineering interviews confidently
Master In Data Engineer Step By Step
- Duration: 3 – 4 Months (Job-Oriented Program)
- Mode: Live + Recorded
- Includes: Real-Time Projects + Placement Support
Introduction to Data Engineering
- What is Data Engineering
- Role of Data Engineer
- Data vs Analytics vs Data Science
- Industry use cases
SQL for Data Engineering
- Database basics
- CRUD operations
- Joins, Group By, Subqueries
- Window functions
- Query optimization
Python for Data Engineering
- Python basics
- Data structures
- File handling
- Working with APIs
- Introduction to Pandas
Data Processing & Transformation
- Data cleaning techniques
- Data transformation
- Working with CSV, JSON
- Data validation
ETL (Extract, Transform, Load)
- ETL concepts
- Data pipeline design
- Scheduling workflows
- Real-time vs batch processing
Data Pipelines
- Building pipelines using Python
- Automating data workflows
- Error handling
- Logging
Big Data Basics
- Introduction to Big Data
- Hadoop ecosystem (overview)
- Spark basics
- Data storage concepts
Cloud Basics for Data Engineering
- Introduction to Cloud (AWS/GCP basics)
- Storage (S3 concepts)
- Data processing tools overview
AI in Data Engineering ⭐
- Using ChatGPT for SQL queries
- Data cleaning with AI
- Debugging pipelines with Copilot
- Automated data insights
Version Control & Workflow
- Git & GitHub
- Collaboration workflows
- Project versioning
Real-Time Projects 🚀
- ETL Pipeline Project
- Data Cleaning Project
- API Data Integration
- Dashboard-ready dataset creation
Master In Data Engineer Step By Step
- Fees
- 50,000 /-
- 2 Installment
- 25,000 + 25,000
- Duration
- 3 – 4 Months (Job-Oriented Program)
- Module
- 11
- Contact
- +91 9209029818
- Payment
- Click to pay
Coming Soon
Programming Language
Python , SQl
Tools
- SQL (MySQL / PostgreSQL)
- Python (Pandas, NumPy)
- ETL Tools (Airflow / Spark Basics)
- Git & GitHub
- Cloud Basics (AWS / GCP)
- Docker / Terraform
- ChatGPT / Copilot
What’s Included ?
Live + Recorded Sessions
Real-Time Industry Projects
Resume & Interview Preparation
Placement Support
Certification
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