Limited Launch offer at 40% discount
DATA ENGINEERING TRACK

Build End-to-End Web Apps with
Python & Modern Tech

Learn to design, develop, and deploy complete web applications through mentor-guided, real-world projects.

Live mentor support
5 real-world projects
Verified portfolio
Project-based assessment
HR-visible skill profile
Start This Track Download Syllabus

Why This Track?

Transform from a beginner to a full stack developer capable of building complex systems. This track covers everything from database design to frontend interactivity.

Backend development using Python
Frontend using HTML, CSS, JavaScript
API development and integration
Database design and management
Authentication and security
Deployment of full-stack applications
Industry-Relevant Projects: Students build complete web systems similar to those used in startups and enterprises.

Who This Track Is For

  • College students (any stream)
  • Beginners in web development
  • Python learners wanting real projects
  • Career switchers into software development
  • Professionals upgrading to full stack roles
Note: No prior coding experience required — Python fundamentals included.

Tools You Will Master

Comprehensive stack for modern web development

Python
Core Language
Django / Flask
Backend Frameworks
FastAPI
High Performance APIs
HTML/CSS/JS
Frontend Basics
React
Frontend Library
MySQL / Postgres
Databases
Git & GitHub
Version Control
Nginx / Docker
Deployment

How You Will Learn

Live Mentor Sessions

Project-led guidance

Weekly Coding Labs

Hands-on practice

Code Reviews

Feedback from experts

Recorded Lessons

Technical concept deep dives

Step-by-step

App building walkthroughs

Doubt Support

Clear your queries

DETAILED SYLLABUS

Curriculum by Program

Choose your learning pace and explore the week-by-week structure.

Data Engineering - Standard (8 Weeks)

Comprehensive 8-week project-based learning curriculum covering all fundamentals and advanced concepts.

Week 1: SQL Mastery & Data Modeling
  • Learning Materials & Concepts
  • Project Activity: SOLO PROJECT 1 START
Week 2: Python for Data Engineering
  • Learning Materials & Concepts
  • Project Activity: SOLO PROJECT 1 DELIVERY
Week 3: ETL/ELT & Orchestration
  • Learning Materials & Concepts
  • Project Activity: SOLO PROJECT 2 START
Week 4: Big Data with Spark
  • Learning Materials & Concepts
  • Project Activity: SOLO PROJECT 2 DELIVERY
Week 5: Streaming & Real\-Time
  • Learning Materials & Concepts
  • Project Activity: PAIR PROJECT START
Week 6: Warehousing & dbt
  • Learning Materials & Concepts
  • Project Activity: PAIR PROJECT DELIVERY
Week 7: Cloud Data Platforms
  • Learning Materials & Concepts
  • Project Activity: GROUP CAPSTONE START
Week 8: Capstone Pipeline & Demo
  • Learning Materials & Concepts
  • Project Activity: GROUP CAPSTONE DELIVERY

Project Roadmap (6 Projects)

From solo builds to team capstones — real-world projects that prove your skills

2 Solo
1 Pair
3 Capstone
Project 1
Solo Project

Serverless Event Streaming Pipeline

API Gateway receiving events -> AWS Lambda/Kinesis -> S3 (Data Lake) -> Athena querying. Handles schema validation and partitioning by date.

API Gateway receiving events -> AWS Lambda/Kinesis -> S3 (Data Lake) -> Athena querying. Handles schema validation and partitioning by date.

💼 Junior Data Engineer. Cloud-native data handling.

Project 2
Solo Project

CDC-based Data Lakehouse with Delta Lake

Debezium reading PostgreSQL WAL -> Kafka -> Spark Streaming -> Delta Lake. Implements ACID transactions on data lake, time travel queries.

Debezium reading PostgreSQL WAL -> Kafka -> Spark Streaming -> Delta Lake. Implements ACID transactions on data lake
time travel queries.

💼 Mid-Level DE. Change Data Capture and Lakehouse architecture.

Project 3
Pair Project

Geospatial Real-Time Tracking Data Mart

Geospatial Real-Time Tracking Data Mart

💼 Senior DE. Geospatial indexing and streaming.

Project 4
Capstone

Unified Customer Data Platform (CDP)

Ingests fragmented identities from Web, CRM, and Support tickets. Deterministic/Probabilistic identity resolution graph. Feeds clean profiles to marketing APIs.

Ingests fragmented identities from Web, CRM, and Support tickets
Deterministic/Probabilistic identity resolution graph
Feeds clean profiles to marketing APIs.

💼 Capstone Project

Project 5
Capstone

Algorithmic Trading Data Ingestion Engine

High-frequency, ultra-low latency ingestion of FIX protocols/WebSocket financial feeds. Windowed aggregations, order-book reconstruction.

High-frequency, ultra-low latency ingestion of FIX protocols/WebSocket financial feeds
Windowed aggregations, order-book reconstruction.

💼 Capstone Project

Project 6
Capstone

Automated Data Governance & Lineage SaaS

Scans warehouse schemas (Snowflake/BigQuery), parses SQL logs to generate visual DAGs of data lineage. PII detection and automated masking policies.

Scans warehouse schemas (Snowflake/BigQuery), parses SQL logs to generate visual DAGs of data lineage
PII detection and automated masking policies.

💼 Capstone Project

Mentor Support & Verification

Our mentors don't just teach — they verify your skills. Every project you build is reviewed, ensuring you meet industry standards before you get certified.

  • Assign project tracks
  • Review code and architecture
  • Verify project completion
  • Approve assessment eligibility
  • Issue recommendation letters
  • Validate portfolio entries
Mentor Verified

Projects Are Not Self-Assessed

"You cannot certify yourself. A working professional mentor must start, review, and approve your work."

PBL Model

Project-Based Assessment Test (PAT) Format

Assessment is based on how you build, improve, and explain projects — not on a single final exam.

Overall Structure (100 Marks)

40 Marks

1. Project Completion & Quality

Evaluated across best 3 projects. Mentor checks problem understanding, implementation, tools, and code quality.

Functionality: 5
Code Quality: 3
UI/UX: 3
Docs: 2
20 Marks

2. Milestone Reviews

Points for regular updates (Design, Mid-build, Final) and fixing mentor feedback. Rewards consistency.
15 Marks

3. DB & API Logic

Evaluation of database schema efficiency, API structure, and data handling logic.
15 Marks

4. Deployment

Live check: Security features (Auth) and successful deployment of the application.
10 Marks

5. Final Defense

Start-to-end explanation of architecture, challenges faced, and problem-solving approach.

Pass Criteria

  • Minimum 60/100 Score
  • All 5 Projects Completed
  • Mentor Verification Done
  • Documentation Submitted

Plagiarism Check

  • Code similarity check
  • Git commit history audit
  • Oral questioning
  • Random live modification

Certification

You only receive the SkillCred Verified Certificate & Recommendation Letter if all criteria are met.

Mentor Rating ≥ 3.5/5 Req

Your Portfolio Output

Your portfolio will show project architecture, GitHub links, technologies used, feature lists, mentor verification, and assessment scores.

HR-Ready Profile

Recruiters can filter candidates based on these specific skills.

Career Outcomes

Python Developer
Backend Developer
Full Stack Developer
Web Application Developer
Software Engineer

HR Corner (Preview)
Recruiter View

HR can filter by:
Python
Django
APIs
Full Stack
[Portfolio Preview Interface]

Frequently Asked Questions

Do I need Python knowledge before joining?

No — Python basics are part of the track.

Will I build real websites?

Yes, all projects are real working web applications.

Is frontend covered?

Yes — HTML, CSS, JavaScript and optional React.

Will deployment be taught?

Yes — students deploy apps on cloud servers.

Start Your Data Engineering Journey

Build apps. Build proof. Build your career.

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