Learn Python in
Weeks, Not Months
Real skills for real data science jobs. No outdated tutorials. Think in logic and use GenAI wisely.
One unique course. One capstone. One career shift.
Stop learning syntax. Start solving real data problems.
Most Python courses teach coding like a developer — not like a data professional.
This program helps you think in logic first, apply Python only where needed, and use GenAI smartly to accelerate real analysis workflows.
In just 8 weeks, you will build practical case-study driven projects, gain confidence in handling real datasets, and develop the portfolio skills companies actually hire for.
Key Outcomes:
- Learn Python specifically for Data Science - not generic programming
- Master real dataset analysis using Pandas, visualization & ML workflows
- Build end-to-end case study projects for a strong job portfolio
- Use APIs & GenAI tools like OpenAI to work on modern AI & data tasks
8 Weeks
Intensive Program
4.9/5
Student Rating
500+
Executives Trained
Become job-ready in Data Science with Python + GenAI.
By Rahim Baig
AI Leader, GenAI Startup Mentor, Educator, Author | Zalando, Flipkart, ZS
Executives from –
Still exploring? Experience the learning before you commit
Join a real, case-study driven preview of the Python for Data Science program.
Understand how analysts think, how modern AI workflows actually work in companies,
and what it truly takes to transition into a data career – with clarity, not confusion.
⚡ Instructor-led recorded walkthrough – practical, concise, zero fluff
Use GenAI to validate your thinking, not replace it.
A Different Approach
Learn how to think like a data scientist. Python is secondary. You'll pick up any language because you understand the logic.
YOU write logic. YOU sketch pseudocode. GenAI validates. This forces thinking—the opposite of the trap.
60% on logic and testing. 40% on code. This ratio builds real understanding—skills that last forever.
Not 7 toy projects. One substantial capstone. Messy, realistic, portfolio-ready. This gets you hired.
Every week: a personal call with a global AI expert. Code reviews, logic validation, capstone polish. This transforms learning.
Sign up for Free Live Webinar - Python for Data Science with GenAI
Experience Mirza Rahim Baig’s teaching style live. Learn how modern data scientists actually work, how GenAI is changing workflows, and what skills you truly need to become job-ready.
- Logic-first approach to learning Python
- Real case study walkthrough
- How to use GenAI tools wisely
- Live Q&A with Mirza
Reserve Your Spot
Built for data pros. Taught by Rahim Baig
AI Strategist • GenAI Startup Mentor • Author • Educator
View his Linkedin
Mirza Rahim Baig brings over 16 years of experience in AI, data science, and analytics leadership, having worked with global organizations and mentored professionals transitioning into high-impact data roles. He has trained teams, guided startups, and helped learners build practical, career-ready analytical capabilities.
As a 3-time author and GenAI mentor, Rahim is known for simplifying complex data science concepts into structured logical frameworks that professionals can immediately apply in real business scenarios.
- 15+ years in AI/ML field
- Author of 3 bestselling books on AI/ML
- Faculty - top MBA & executive programs
- GenAI startup advisor and mentor
- Named Top 100 Global AI Leader
Previously worked at:
Course Trainer at:
Secure your place in the next cohort and begin your journey
towards practical Python, AI, and data science expertise.
Secure your place in the next cohort and begin your journey-
Towards practical Python, AI, and data science expertise.
Student Testimonials
Real Projects. Real Confidence. See how learners became data-science ready with logic-first Python training.
"The logic-first teaching style helped me truly understand data analysis instead of blindly copying Python code."
"Weekly case studies made learning practical. I built real projects using Pandas, ML models and modern AI tools."
"Understanding APIs and GenAI workflows gave me strong industry-relevant skills. This course feels very future-ready."
"The mentorship and structured assignments pushed me to think like a real data scientist. Great portfolio boost."
"Rahim simplifies complex ML and data concepts in a very logical way. The pseudocode approach made learning faster."
"Unlike generic tutorials, this program focuses on end-to-end data workflows. I now feel confident handling real datasets."
"Great balance of Python fundamentals, visualisation and machine learning. Helped me move from Excel analytics to real data science."
Inside the Program Curricullum
An 8-Week Live Cohort to Build Job-Ready Data Science Skills.
8 Weeks
Program Duration
16+ Hours
Live Interactive Sessions
2 Projects
Real Data Case Studies
Certificate
Upon Successful Completion
The Case Study, Foundations, Your First Program
Apr 11—Apr 12 • Class: SUN 4/12, 6:00 PM—8:00 PM (GMT+5:30)
- Python's role in modern data science and AI.
- DS Python vs. software development roles.
- Set up environment (Google Colab) and master tools.
- Start first case study; use GenAI effectively for coding.
- Unlock the secret sauce: pseudocode for DS tasks.
- Use Gemini in Colab as coding assistant.
- Solving your first mini case study.
Python Elements: Variable Types and Conditionals
Apr 13—Apr 19 • Class: SUN 4/19, 6:00 PM—8:00 PM (GMT+5:30)
- Atomic and collection data types.
- Master variables and data types (lists, strings, numbers).
- Indexing, list and string manipulation.
- Implement business logic using control structures (if-else).
- Write clear pseudocode before coding.
- Conditional logic for data filtering and categorization.
- Mini case study.
Loops and Functions – Don't Repeat Yourself
Apr 20—Apr 26 • Class: SUN 4/26, 6:00 PM—8:00 PM (GMT+5:30)
- Understand the need for loops/functions.
- Write pseudocode for iterative logic.
- Automate tasks with loops.
- Abstract logic into modular pieces.
- Create reusable code with custom functions.
- Build custom functions for analysis.
- Refactor case study code using functions.
Data Analysis Fundamentals with Pandas
Apr 27—May 3 • Class: SUN 5/3, 6:00 PM—8:00 PM (GMT+5:30)
- Series and DataFrames in Pandas library.
- Import & explore data from various formats (CSV, XLSX, etc.).
- Efficiently filter and select data.
- Understand and prepare data structure.
- Navigate DataFrames using indexing.
- Filter data based on conditions.
- Explore data with basic statistics.
Data Transformation and Aggregation
May 4—May 10 • Class: SUN 5/10, 6:00 PM—8:00 PM (GMT+5:30)
- Lesson topics to be revealed later...
Data Visualization and EDA
May 11—May 17 • Class: SUN 5/17, 6:00 PM—7:30 PM (GMT+5:30)
- Introduction to Matplotlib.
- Basic plot types (line, scatter, bar, histogram).
- Plot customization and styling.
- Saving and exporting visualizations.
- Seaborn for statistical visualization.
- Interactive visualization tools.
- Customizing color palettes and themes.
- Visualization best practices.
Machine Learning with Scikit-Learn
May 18—May 24 • Class: SUN 5/24, 6:00 PM—8:00 PM (GMT+5:30)
- EDA specifically for Machine Learning.
- Use the versatile sklearn package.
- Handling categorical values.
- Split data into training and testing sets.
- Build a logistic regression model.
- Evaluate model performance (accuracy, precision, recall).
Real-World Data with APIs & Course Closure
May 25—May 31 • Class: SUN 5/31, 3:30 PM—4:30 PM (GMT+5:30)
- Lesson topics to be revealed later...
Any Questions?
Ask the instructor directly
Book a direct conversation with global AI Expert & Leader- Mirza Rahim Baig
Target Career Paths
Roles you will be ready to step into from day one.
Data Analyst
Dashboards & Insights
Jr. Data Scientist
ML Models & EDA
Business Analyst
Strategy & Visualization
ML Associate
APIs & Pipelines
Frequently Asked Questions
Everything you need to know about the Python for Data Science with GenAI program
Who is this course designed for?
This program is ideal for graduates, working professionals, and career switchers who want to build real data science and AI skills. It is especially useful for those who want practical, job-ready experience rather than only theoretical learning.
What's the time commitment
The course runs for 8 weeks with around 2 hours of live sessions per week, along with 3–4 hours of assignments and case study practice. Consistent weekly effort is recommended to maximise learning outcomes.
Do I need technical AI knowledge?
No prior experience in Python, data science, or AI is required. The course follows a logic-first beginner friendly approach, making it suitable even for learners from non-technical backgrounds.
What format is the course delivered in?
The program is delivered through live interactive online sessions, hands-on case studies, project assignments, and weekly mentorship guidance. Recordings are also available for revision.
Is there support after the course?
Yes. You will retain lifetime access to learning materials and recordings, along with continued guidance for project portfolio development and career progression direction.
What if I can’t attend live sessions?
All sessions are recorded and shared with participants. You can watch them later and continue with assignments and mentorship support without missing key learning.
How is this different from other AI courses?
Unlike tutorial-based programs, this course focuses on real problem solving, structured analytical thinking, and practical project execution, while using GenAI as a productivity tool — not a shortcut.
What if I get doubts?
You will have weekly mentorship touchpoints, assignment feedback, and peer community interaction to clarify doubts and stay on track throughout the program.
Spots Are Filling Fast - Secure Your Seat Before the Next Live Cohort
Join the free live webinar to experience how the course works, see real case study demonstrations, and understand how you can build practical Python and data science skills using a logic-first learning approach.
🔥 Only limited seats available for the upcoming cohort
⚡ Recorded guide available from instructor • No jargon
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