Tech IT SolutionData Science with Python
Learn end-to-end data science using Python — data wrangling, visualization, statistics, machine learning, model deployment & real-world projects for data analyst / scientist roles
Why join this course
Learn data science the practical way: Python-first, project-heavy and built for beginners. Go from Pandas and statistics to machine learning models, with 12+ end-to-end projects that make your portfolio stand out.
Python-first approach
Learn the exact libraries data teams use every day.
12+ portfolio projects
Churn, house prices, sentiment analysis and more.
Beginner friendly
Every concept is taught from the basics with guided practice.
Clear career path
A launchpad into analyst and junior data scientist roles.
By the end you will be able to
- Python for Data Science (Pandas, NumPy, Matplotlib, Seaborn)
- Exploratory Data Analysis (EDA) & Data Cleaning
- Statistics & Probability for Data Science
- Machine Learning Algorithms (Regression, Classification, Clustering)
- Model Evaluation, Hyperparameter Tuning & Cross-Validation
- SQL for Data Science & Big Data Basics
- 12+ End-to-End Projects (Customer Churn, House Price Prediction, Sentiment Analysis...)
Who is this course for?
Add a job-ready skill next to your degree or diploma.
Upskill for a promotion, a better role or a career switch.
Use these skills to deliver client work or run your own business better.
Curriculum overview
6 modules, explained in detail. Open a module to see exactly what is inside.
1Python for Data Science7 topics
Get fluent with the core Python data stack: arrays, DataFrames, loading and indexing data from files.
What is inside
- Python basics refresh
- NumPy arrays & operations
- Pandas DataFrames
- Data loading (CSV, Excel, JSON)
- Indexing & slicing
- GroupBy
- Merge & Join
2Data Wrangling & Exploratory Data Analysis (EDA)7 topics
Real data is messy. Learn to clean it, spot outliers, engineer features and explore relationships.
What is inside
- Handling missing values
- Outlier detection
- Data transformation
- Feature engineering
- Univariate & bivariate analysis
- Correlation
- Pandas profiling
3Data Visualization4 topics
Make patterns visible with Matplotlib, Seaborn and Plotly, and get a first look at dashboards with Streamlit.
What is inside
- Matplotlib basics
- Seaborn (pairplot, heatmap, violin, box)
- Plotly for interactive charts
- Dashboard concepts with Streamlit intro
4Statistics & Probability for Data Science7 topics
The statistics behind good decisions: distributions, hypothesis tests, p-values and confidence intervals.
What is inside
- Descriptive stats
- Probability distributions
- Hypothesis testing
- P-value
- Confidence intervals
- A/B testing basics
- Correlation vs Causation
5Machine Learning Fundamentals6 topics
Your first machine learning models: regression, classification and clustering, with proper train-test evaluation.
What is inside
- Supervised vs Unsupervised
- Train-test split
- Regression (Linear, Ridge, Lasso)
- Classification (Logistic, Decision Trees, Random Forest, SVM)
- Clustering (K-Means)
- Model evaluation metrics
6Advanced ML, Deployment & Projects8 topics
Level up with ensembles, tuning and deployment, then apply everything in end-to-end projects.
What is inside
- Ensemble methods (XGBoost, LightGBM)
- Feature selection
- Hyperparameter tuning (GridSearch, RandomSearch)
- Model deployment (Flask/Streamlit)
- SQL for data extraction
- 12+ end-to-end projects
- Capstone project
- Portfolio & job prep (Kaggle, GitHub)
What you will build
Real work for your portfolio, not just exercises.
Customer churn prediction
Identify customers likely to leave and explain why.
House price prediction
Build a regression model and tune it for accuracy.
Sentiment analysis
Classify reviews as positive or negative with text features.
Tools you will use
How you will learn
Career outcomes
Roles this course prepares you for:
- Resume & LinkedIn profile building
- Portfolio and project review
- Mock interviews with IT leads
- Hiring-partner drives and referrals
Certificate, batches & details
W Tech Data Science with Python Certification + Portfolio
Issued after you pass the final evaluation of the course.
Flexible batches
Morning, afternoon, evening and weekend batches. Classroom at GTB Nagar or live online.
Course at a glance
| Duration | 5–6 months (Flexible batches) |
|---|---|
| Level | Beginner to Advanced |
| Mode | Classroom (GTB Nagar, Delhi) & live online |
| Teaching format | Live Sessions + Capstone Projects |
| Prerequisites | No prior experience needed. We start from the basics and build up step by step. |
| Batches | Weekday morning / afternoon / evening & weekend |
| Certificate | W Tech Data Science with Python Certification + Portfolio |
| Fees | Call or WhatsApp for the current fee · EMI options available |
Frequently asked questions
Who can join Data Science with Python?
No prior experience needed. We start from the basics and build up step by step. Students, graduates, job seekers and working professionals are all welcome.
How long is the course and what are the batch timings?
The course runs for 5–6 months (Flexible batches). We run weekday morning, afternoon and evening batches plus weekend batches for college students and working professionals.
Are classes online or in the classroom?
Both. Attend live in our GTB Nagar (Delhi) classroom or join live instructor-led online classes from anywhere in India. Sessions are recorded, and you can switch between modes.
What certificate will I receive?
W Tech Data Science with Python Certification + Portfolio, awarded after you pass the final evaluation.
Will I work on real projects?
Yes. Most of the training is hands-on labs and guided projects, and you finish with work you can show in your portfolio.
What jobs can I apply for after this course?
Typical roles include Junior Data Scientist, Python Data Analyst, ML Associate. Your outcome depends on your skills, portfolio and interview performance, and our placement team supports you at every step.
Do you help with placement?
Yes. We help with resume and LinkedIn profiles, portfolio review, mock interviews and hiring-partner drives. This is placement assistance, not a job guarantee.
What is the fee, and is EMI available?
Fees depend on the batch and mode. Call or WhatsApp us for the current fee and flexible EMI / installment options.
Can I attend a free demo class first?
Yes. Book a free demo class to meet the mentors and see how the training works before you enrol.
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