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100%
Production Project Focus
1-on-1
Mentorship & Code Reviews
20+
Hands-On DE & AI Modules
Direct
Placement Panel Referrals
Built for Career Transition
Why Choose TWS Academy?
We eliminate the gap between theoretical textbook coding and real-world enterprise engineering standards.
Next-Gen Curriculum
AI-Native Data Curriculum
Learn Data Engineering natively integrated with Generative AI infrastructure, vector search engines, RAG orchestration, and automated LLM pipelines.
- Vector Search & Semantic Retrieval Architectures
- Autonomous LLM Agent Orchestration with LangChain
- Scalable Prompt & Model Deployment Pipelines
Real Engineering
Production-Grade Capstones
Build live data streaming engines with Apache Kafka, PySpark, Airflow DAGs, and Snowflake on AWS/GCP — real portfolios that impress tech directors.
- Real-Time Streaming Pipelines with Kafka & Flink
- Batch & Delta Lake Processing via PySpark
- Enterprise Airflow DAGs & Cloud Data Warehousing
Career Transition
Direct Placement Cell
1-on-1 mock interviews with active tech hiring managers, resume transformation, communication skill training, and corporate referral support.
- Active Hiring Manager Technical Mocks
- Direct Corporate Referral Network Access
- High-Impact Resume & Github Portfolio Revamp
Structured Curricula
View All CoursesFeatured Training Programs
01Core Track
Data Engineering
SQL, Python, Spark aur cloud pipelines — job-ready, project-first.
Duration:Announced per batch
Level:Beginner-Friendly
Format:Live batches + recorded lessons
SQLPythonPySparkData modelling
Fee planOn request
View Full Syllabus02Flagship — AI
Data Engineering with AI
Core data engineering plus the AI tooling employers now expect.
Duration:Announced per batch
Level:Intermediate → Advanced
Format:Live batches + recorded lessons
Everything in Data EngineeringLLM APIsEmbeddings & vector searchAI pipeline design
Fee planOn request
View Full Syllabus03Career Skills
Communication Skills
Interviews, meetings aur workplace English — practice-first.
Duration:Announced per batch
Level:All Levels
Format:Live practice sessions
Interview answersMeeting EnglishPresentation basicsConfidence under pressure
Fee planOn request
View Full SyllabusStep-by-Step Journey
Your Transformation Roadmap
How we guide you from enrollment to landing your target engineering job.
Step 01
Foundations & Core Engineering
Master Advanced SQL, Python OOP, Linux environment scripting, and relational data modeling with hands-on daily coding drills.
Step 02
Distributed Big Data & Warehousing
Scale pipeline processing with PySpark, partition big datasets, deploy Airflow DAGs, and structure cloud warehouses on Snowflake/BigQuery.
Step 03
Generative AI & Vector Search Infrastructure
Integrate Vector Databases (Pinecone, Milvus), chunk unstructured text/audio data, build RAG pipelines, and deploy LLM microservices.
Step 04
Production Capstone & Portfolio Review
Architect an end-to-end cloud production system, document GitHub repository clean code standards, and complete mentor code reviews.
Step 05
Mock Interview Panel & Placement Referral
Participate in 1-on-1 mock technical interviews with tech leads, refine your communication skills, and enter our corporate referral pipeline.
Real Production Experience
Practical Capstone Projects
No toy datasets. You build enterprise-ready architectures that prove your capability during interviews.
Real-Time Streaming & Analytics
Real-Time Transaction Fraud Detection Pipeline
High-throughput event streaming engine that ingests thousands of transactions per second, evaluates fraud scores via Spark Structured Streaming, and alerts analysts.
Key Features:
- Sub-second transaction ingestion & validation
- Distributed windowed analytics in Spark
- Automated alert triggers for suspicious patterns
Apache KafkaPySparkDockerPostgreSQLGrafana
Generative AI Infrastructure
Enterprise Knowledge Graph & Vector RAG Pipeline
Unstructured document pipeline that parses thousands of PDF reports, generates semantic embeddings, and powers a context-aware internal Q&A agent.
Key Features:
- Automated PDF parsing & semantic chunking
- Hybrid dense–sparse vector search
- Hallucination prevention & source citation
PythonVector DBLangChainFastAPIDocker
Data Warehousing & Orchestration
Automated Multi-Cloud Warehouse ETL Orchestration
Production Airflow DAG network ingesting REST API data, transforming raw JSON into star-schema models, and loading into a cloud warehouse with quality checks.
Key Features:
- SCD Type 2 history tracking for dimensions
- Automated data validation rules
- CI/CD DAG deployment
Apache AirflowSnowflakedbtPythonAWS S3
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