Data Science · Course Guide · Full Breakdown
Uncodemy Data Science Course — Everything You Need to Know
Quick summary — the Uncodemy Data Science course
The Uncodemy Data Science course is a 24-week, live-mentored programme covering Python, SQL, statistics, classical ML, deep learning, LLMs, MLOps and deployment — ending with a deployed capstone project and structured placement support. It's designed for beginners and career-changers with basic IT or analytical skills (no prior ML needed). Fees are ₹38,500. Entry salary in Delhi NCR is ₹5–10 LPA; with 2–3 years of experience, ₹12–22 LPA is realistic. The course is honest about placement — it provides resume support, mock interviews and hiring-partner referrals, but doesn't guarantee jobs. The capstone project is the single most important part — it's what interviewers ask about.
In this guide you will learn:
- The full curriculum — module by module, with hours.
- The three phases — foundation, ML + DL, capstone.
- Tools you'll actually use — Python, SQL, PyTorch, Docker.
- Fees, faculty and placement support — honest breakdown.
- Interview Q&A + quiz to check your understanding.
SECTION 01Who is this course for?
The Uncodemy Data Science course is designed for people entering or moving into data roles. Honest fit:
| Profile | Fit | Why |
|---|---|---|
| Engineering graduate | Excellent | Analytical background + programming basics give a head start |
| BCA / MCA student | Excellent | Already familiar with programming and databases |
| Data / business analyst | Excellent | Career progression into data science |
| Non-tech graduate (B.Com, BA, B.Sc) | Good | Learnable — needs extra time on Python and stats |
| Working professional (any field) | Good | Weekend batches designed for working people |
| 12th-pass student with no college | Not ideal | Build foundational maths/CS first — this is a career-level course |
SECTION 02The full curriculum
The course is 24 weeks across the three phases. Here's the complete module list:
| Module | Topics | Duration |
|---|---|---|
| Python basics | Syntax, data types, functions, OOP, file handling, virtual envs | 2 weeks |
| Data analysis | NumPy, Pandas, data cleaning, EDA, visualisation (Matplotlib, Seaborn) | 3 weeks |
| SQL | SELECT, JOINs, aggregations, window functions, CTEs | 2 weeks |
| Statistics | Descriptive stats, hypothesis testing, A/B testing, distributions | 2 weeks |
| Classical ML | Regression, classification, clustering, tree-based models, model evaluation | 4 weeks |
| Deep learning | Neural networks, CNNs, RNNs, PyTorch | 3 weeks |
| LLMs + RAG | Prompt engineering, OpenAI/Anthropic APIs, RAG, vector DBs | 2 weeks |
| MLOps + deployment | Docker, FastAPI, cloud basics, model monitoring | 2 weeks |
| Capstone project | End-to-end deployed project with documentation | 4 weeks |
SECTION 03The three phases
The course is structured in three phases — each with a specific goal:
| Phase | Weeks | Focus | Output |
|---|---|---|---|
| Foundation | 1–8 | Python, SQL, stats, EDA | Can analyse and clean data |
| ML + DL | 9–18 | Classical ML, deep learning, LLMs | Can build and evaluate models |
| Capstone + Career | 19–24 | Deployment, portfolio, interviews | Job-ready with a real project |
SECTION 04Tools and projects
You'll use professional-grade tools — the same ones used in industry:
- Python 3.11+ — the entire course runs on Python.
- Jupyter notebooks + VS Code — the standard dev environments.
- Pandas, NumPy, Matplotlib, Seaborn — for data analysis.
- scikit-learn, XGBoost — for classical ML.
- PyTorch — for deep learning.
- LangChain, OpenAI/Anthropic APIs, ChromaDB — for LLM + RAG.
- Docker, FastAPI — for deployment.
- PostgreSQL / BigQuery — for SQL.
- Git + GitHub — for version control and portfolio.
- MLflow — for experiment tracking.
The capstone project is a real, deployed ML application — not a notebook. Common capstone themes from past batches:
- Churn prediction — predict customer churn for a telecom or SaaS dataset, deploy as an API.
- Price prediction — real estate or e-commerce pricing model with a FastAPI endpoint.
- Document Q&A with RAG — LLM-powered assistant over a corpus of documents.
- Fraud detection — imbalanced classification with proper evaluation.
- Recommendation system — collaborative filtering with a simple UI.
SECTION 05Fees, faculty and placement
The honest breakdown of what the course costs and what you get:
| Attribute | Details |
|---|---|
| Course fee | ₹38,500 · no hidden costs |
| Duration | 24 weeks (6 months) |
| Format | Live classes + lab exercises + capstone |
| Batches | Weekday (7:00 PM) and weekend (Saturday 10 AM) |
| Faculty | Industry practitioners with real ML/data backgrounds |
| Mentorship | 1:1 during capstone project |
| Career support | Resume rebuild, mock interviews, hiring-partner referrals |
| Batch repeats | Free lifetime repeat access |
| Projects | 2–3 mini projects + 1 end-to-end capstone |
| Certificate | Yes, on successful completion |
Salary progression for Uncodemy graduates (Delhi NCR, realistic):
| Experience | Data Analyst | Data Scientist | ML Engineer |
|---|---|---|---|
| Fresher (0–1 yr) | ₹5–8 LPA | ₹6–10 LPA | ₹7–11 LPA |
| 1–3 yrs | ₹8–15 LPA | ₹10–18 LPA | ₹12–22 LPA |
| 3–5 yrs | ₹15–25 LPA | ₹18–30 LPA | ₹22–35 LPA |
| 5+ yrs | ₹25–42 LPA | ₹30–50 LPA | ₹35–60 LPA |
SECTION 06Interview Q&A — about the course
Q1Do I need prior programming experience?
No — but basic familiarity with any programming language helps. We include a Python pre-work module that brings beginners up to speed. If you're completely new to programming, budget 2–3 extra weeks before starting to complete the pre-work properly.
Q2Which topics does the course actually cover?
The full modern data science stack: Python, Pandas, NumPy, Matplotlib, SQL, statistics, classical ML, deep learning (PyTorch), LLMs + RAG, MLOps, Docker, and deployment. The capstone is end-to-end and deployed — not just a notebook.
Q3Is the course recorded or live?
Live. All sessions are live with Q&A. You'll also get access to recordings afterwards for revision. Small batch sizes mean real attention from the trainer, not just broadcast lectures.
Q4Do you guarantee placement?
No — and no honest institute should. We provide resume rebuilds, mock interviews, portfolio review, and introductions to 14+ hiring partners. Whether you get placed depends on your effort, the market, and your interview performance. We're honest about this.
Q5Can I take this course while working full-time?
Yes — the weekend batch (Saturday 10 AM) is designed for working professionals. Many of our students are working in adjacent roles (analyst, developer, QA) and transition into data science. The weekend batch adds about 2–3 weeks to the total duration.
SECTION 07Test yourself — the course
Five questions. No sign-up.
0 / 5Pick an answer to see why it is right or wrong.
SECTION 08Frequently asked questions
How long is the Uncodemy Data Science course?
24 weeks (6 months) total. Weekend batch adds about 2–3 weeks. Includes capstone project and career prep.
What's the course fee and are there hidden costs?
₹38,500 for the full programme. No hidden costs — the fee includes all classes, materials, project mentorship, and placement support. There's no "premium tier" or "advanced add-on" charge. What you see is what you pay.
What certifications does the course prepare me for?
The course itself includes an Uncodemy certificate on completion. It also prepares you for broader certifications like Google Professional Data Engineer, AWS ML Specialty, or Azure AI Engineer — but those exams are separate costs and optional.
Do I need to buy any software or hardware?
No. Everything you need is free and open source: Python, VS Code, PyTorch, scikit-learn, Docker. For deep learning you can use Google Colab's free GPU tier for training. A laptop with 8GB RAM is enough for most work.
What if I want to compare Uncodemy with other institutes?
Please do. Compare us on curriculum, faculty, projects, placement honesty and fees. Ask each institute for a syllabus PDF, a trainer call, project samples and alumni contacts. We'd rather you choose us having done the comparison than sign up blind.
SECTION 09Related reads
Classroom & online · Noida
Data Science programme — 24 weeks, three phases
Our Data Science programme covers Python, SQL, ML, deep learning, LLMs, MLOps and deployment — with live mentorship, a deployed capstone project and structured placement support.
₹38,500 · per programme- Live classes + Q&A
- Deployed capstone project
- 1:1 placement support
- Weekday & weekend batches