Data Science with Python
From Python basics to machine learning and GenAI — build a portfolio that gets interviews.
About this program
Why this career pays off
Data skills are now expected in every industry, and Python is the language of that world. This program takes you from programming fundamentals through statistics, machine learning and an introduction to generative AI — with portfolio projects on real datasets, because in data science interviews your projects do the talking.
What you'll learn, module by module
A complete, no-surprises view of the curriculum. Click any module to expand.
01 Python Programming
- Syntax, data types, control flow
- Functions and modules
- File handling and error handling
- Object-oriented basics
02 Data Handling with pandas & NumPy
- Arrays and vectorised computation
- DataFrames: cleaning, joining, reshaping
- Handling missing and messy data
- Real dataset workout
03 Statistics for Data Science
- Descriptive statistics and distributions
- Probability essentials
- Hypothesis testing
- Correlation vs causation
04 Data Visualisation
- Matplotlib and styling
- Charts that answer business questions
- Dashboards overview (Power BI)
- Storytelling with data
05 SQL for Analysts
- Queries, joins and aggregation
- Window functions
- Database design basics
- SQL + Python together
06 Machine Learning I
- Supervised learning: regression and classification
- Train/test methodology and metrics
- scikit-learn workflow
- Feature engineering
07 Machine Learning II
- Tree ensembles and boosting
- Unsupervised learning: clustering
- Model tuning and validation
- Avoiding overfitting
08 GenAI Foundations
- How LLMs work at a high level
- Using LLM APIs from Python
- Prompting for data tasks
- Where GenAI fits in analytics work
09 Capstone: Portfolio Projects
- End-to-end project on a real dataset
- GitHub portfolio and presentation
- Interview preparation: explaining your models
- Mock interviews with industry experts
Who this program is for
- Graduates from any stream comfortable with logical thinking
- Professionals in analytics-adjacent roles (MIS, reporting, finance)
- Engineers and BCA/MCA graduates targeting data roles
- Career switchers who prefer analysis to infrastructure
Roles you can target after
- Data Analyst
- Junior Data Scientist
- Business Analyst (technical)
- ML Engineer (entry track)
- Python Developer (data)
Tools & technologies covered
Python Jupyter NumPy pandas Matplotlib scikit-learn SQL Power BI (overview) Git LLM APIs (introduction)
Common questions
SHA Cloud Career Path ?
Foundation ->Cloud Administration ->Cloud Support / Junior Cloud Engineer ->Cloud Engineer ->Senior Cloud Engineer->Cloud / Solutions Architect
Database Architect path?
Database Foundation:→ Junior DBA / Database Support→ DBA→ Senior DBA / Database Engineer→ Database Architect
Can I directly work as Database Architect?
No, not at all. Below is the path you have to follow:
Database Foundation:→ Junior DBA / Database Support→ DBA→ Senior DBA / Database Engineer→ Database Architect
Can I joined directly as Cloud Architect?
No, Not at all.
Foundation ->Cloud Administration ->Cloud Support / Junior Cloud Engineer ->Cloud Engineer ->Senior Cloud Engineer->Cloud / Solutions Architect
Don't Know Which IT Career Is Right for You?
You don't need to choose a technology before understanding the career. Your IT Career Map:
Graduate->Understand your background & strengths->Choose a direction->If you enjoy...Infrastructure, systems, servers, then a possible path is Cloud / Infrastructure-> If you enjoy...Databases, data, backend systems, then a possible path is Database / Cloud DBA. If you enjoy...Programming + mathematics + analytics, then a possible path is Data / AI. If you enjoy...Automation + infrastructure, then a possible path is DevOps / Cloud Engineering. If you enjoy...Security & systems, then a possible path is Cloud Security / Cybersecurity. If you enjoy...Multiple cloud platforms, then a possible path is Multi-Cloud / Gen & Agentic AI and on ......Final steps once you decide: Foundation → Specialisation → Projects → Interview Preparation → Job Search _> Got placement. So you need one mentor for this guidance who himself works in the IT Industry that to minimum of 10- 12 years.