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Journey Map

Data Science with Generative AI & Agentic AI

The complete 230-day journey — every phase, every week, every exam, every placement drive. This is how you'll actually spend the next 7.5 months.

Total Duration
230 Days
~7.5 months · 33 weeks
Total Phases
8
4 learning + 4 learning & internship
Learning Track
25 Weeks
Phases 1–4
Learning & Internship
8 Weeks
Phases 5–8
Total Exams
33
Every Saturday
Interviews Per Month
8+
During the placement phase
Weekly Rhythm

Two phases. Two completely different weeks.

Your day-to-day changes dramatically after Week 25. Here's exactly what a week looks like in each phase.

Learning Track

Phase 1 · Weeks 1 – 25

Learning & Foundation

Deep-dive into core concepts, coding, aptitude, and communication.

Monday – Friday
  • 1 hr 30 min live class
    Core subject deep-dive
  • Practice sessions
    Hands-on coding lab
  • Assignments
    Daily submissions
  • Communication training
    GD · JAM · presentations
  • Aptitude & reasoning
    Interview-grade problem solving
  • Daily activities
    LinkedIn · GitHub · workshops
Saturday
Weekly Exam
Sunday
Rest / Revision
Learning & Internship Track

Phase 2 · Weeks 26 – 33

Learning & Paid Internship

Keep learning the remaining modules while you complete a PAID internship — plus mocks and drives.

Monday – Friday
  • Placement classes
  • Remaining modules
    Continue learning alongside work
  • PAID internship — 6 hrs / day
    Stipend-based, real projects at The Skill Union
  • Interview preparation
    Technical + HR rounds
  • Mock interviews
    Weekly recorded reviews
  • Resume + portfolio building
    LinkedIn · GitHub polish
  • Company interview drives
    8+ opportunities / month
Saturday
Drive / Interview
Sunday
Rest / Revision
Master Timeline

8 phases. 2 tracks. 1 outcome.

1
Python
Weeks 1 – 9
2
Machine Learning
Weeks 10 – 16
3
Deep Learning
Weeks 17 – 21
4
NLP
Weeks 22 – 25
5
Excel
Week 26
6
Power BI
Weeks 27 – 29
7
Tableau
Weeks 30 – 31
8
SQL
Weeks 32 – 33
Learning Track (Phases 1–4) Learning & Internship Track (Phases 5–8)
Learning Track

Phases 1 – 4 · Foundation to Frontier AI

25 weeks · ~5.5 months · concepts + mini projects each phase

1
Phase 1 · Weeks 1 – 9

Python, Statistics & Mathematics

  • Python Fundamentals
  • Advanced Python (multiprocessing & multithreading)
  • Statistics — hypothesis testing, Bayes, distributions
  • Mathematics — matrix algebra, eigenvalues, regression
  • NumPy & Pandas
  • Data Visualization — Matplotlib & Seaborn
  • SQL Basics
  • Web scraping
  • Problem Solving & DSA
Hands-on Projects

Python Mini Projects

  • 1Real-Time Stock Market Data Pipeline (API → ETL → Alerts)
  • 2Automated Invoice & Document Processing Engine
  • 3Multi-Threaded Web Scraper for Competitor Price Intelligence
  • 4Event-Driven Order Processing Microservice (RabbitMQ)
  • 5Retail Sales Data Warehouse Loader with Data-Quality Checks
2
Phase 2 · Weeks 10 – 16

Machine Learning

  • Regression
  • Classification
  • Clustering
  • Feature Engineering & PCA
  • Model Evaluation
  • Hyperparameter Tuning
  • Ensemble Learning — Random Forest, XGBoost, AdaBoost
  • KNN, Naive Bayes, Decision Trees, SVM
  • Deployment Basics
Hands-on Projects

Machine Learning Projects

  • 1Credit Card Fraud Detection on Imbalanced Transaction Data
  • 2Telecom Customer Churn & Lifetime-Value Intelligence
  • 3Demand Forecasting Engine for Multi-Store Retail Inventory
  • 4Hybrid Product Recommendation System (Collaborative + Content)
  • 5Loan Default Risk Scoring with Explainable AI (SHAP)
Industry Bridge · Starts after Phase 2

Enter The Skill Union — build like a real engineer.

Once you've cleared ML fundamentals, you're plugged into industry-grade projects at The Skill Union — Vihara Tech's in-house product studio. Real teams, real tickets, real GitHub commits.

Visit The Skill Union
Industry projects
Portfolio building
GitHub development
Team collaboration
Real workflows
Hands-on labs
3
Phase 3 · Weeks 17 – 21

Deep Learning, CV & OpenCV

  • Neural Networks — neurons, backprop, activations
  • TensorFlow
  • Keras
  • CNN — VGG16/19, ResNet
  • RNN
  • LSTM
  • Transfer Learning
  • Computer Vision — YOLO v1–v8, segmentation, pose estimation
  • OpenCV — image processing & transformations
  • NLP Fundamentals
Hands-on Projects

Deep Learning Projects

  • 1Smart Retail Video Analytics — Footfall, Queue & Shelf Monitoring
  • 2Industrial Defect Detection on Production Lines (YOLO + Segmentation)
  • 3Medical Imaging Diagnosis Assistant with Transfer Learning
  • 4Intelligent Document Extraction (OCR + Transformer Understanding)
  • 5Driver Safety Monitoring — Pose, Drowsiness & Distraction Detection
4
Phase 4 · Weeks 22 – 25

NLP, GenAI & Agentic AI

  • LLM Fundamentals — Transformers, BERT, GPT
  • Prompt Engineering & structured outputs
  • RAG (Retrieval-Augmented Generation)
  • Vector Databases
  • LangChain
  • AI Agents
  • MCP (Model Context Protocol)
  • Multi-Agent Systems — CrewAI, AutoGen, LangGraph
  • Agentic AI workflows
  • Fine-tuning (LoRA / QLoRA)
  • Deployment — FastAPI + Docker
Hands-on Projects

Generative AI & Agentic AI Projects

  • 1Production-Grade Enterprise RAG Assistant (Hybrid Search + Re-ranking)
  • 2Multi-Agent Autonomous Research & Market-Intelligence System
  • 3AI Workflow Automation Agent with Tool Calling & MCP Integrations
  • 4Domain Fine-Tuned LLM (LoRA/QLoRA) with Guardrails & Evaluation Suite
  • 5Multimodal AI Analyst — Documents, Images & Dashboards (FastAPI + Docker)
Learning & Internship Track

Phases 5 – 8 · Remaining Modules + Paid Internship

8 weeks · Excel · Power BI · Tableau · SQL — learned alongside your paid internship

5
Phase 5 · Week 26
Excel
Business analytics foundation
  • Formulas, LOOKUP / INDEX-MATCH
  • PivotTables, charts, conditional formatting
  • Named ranges, text & date functions
6
Phase 6 · Weeks 27 – 29
Power BI
Enterprise dashboards
  • Power BI Desktop & data modeling
  • DAX formulas & visualizations
  • Power Query & Model View
7
Phase 7 · Weeks 30 – 31
Tableau
Data storytelling
  • Sheets, dashboards, storytelling
  • Parameters, sets & chart types
  • Publishing production reports
8
Phase 8 · Weeks 32 – 33
SQL
Data engineering essentials
  • SELECT, JOINs, GROUP BY / HAVING
  • Subqueries, UNION, views & indexes
  • Transactions, constraints, DML
PAID Internship · Stipend-Based · The Skill Union

Get paid to work on real client projects — before you're even placed.

For all 8 weeks of this track you're on a live team — 6 hours a day, PAID internship, shipping code that goes to production, while you finish your remaining modules. It's the difference between "0 years experience" and "already worked on a live product" on your resume.

Industry Internship
Live team, live product
Real Client Projects
Tickets, sprints, PRs
Team Collaboration
Daily standups & reviews
Daily Task Assignments
Tracked & measurable
Mentor Reviews
1:1 code feedback
Performance Evaluation
Formal appraisals
Portfolio Building
Shippable case studies
Interview Readiness
Story-driven answers
Placement Support
8+ interviews / month

Want to see the Placement Preparation?

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