Master Data Science & Machine Learning Using Python
A Complete Beginner-to-Professional Course by Muhammad Hassaan
Certified by LUMS Centre for Continuing Education Studies
Why This Course Exists?
Data Science and Machine Learning are no longer just buzzwords — they are the backbone of modern business, technology, and research. Yet most online courses are either too theoretical, too expensive, or simply not designed for students from Pakistan and South Asia.
This course is built from real, hands-on experience in Data Science and Machine Learning — not just theory. The focus is simple: learn by doing. Instead of long lectures, you’ll work on practical tasks, real-world examples, and guided projects that help you actually apply what you learn. The goal is to give you industry-relevant skills in a way that is engaging, easy to follow, and truly useful for students across Pakistan and South Asia.
Who Is This Course For?
This course is perfect for:
- Students and fresh graduates looking to enter the data field
- Working professionals who want to upskill and shift careers
- Freelancers looking to offer data analysis and ML services
- Anyone curious about Python, AI, and data — with zero prior experience required
What You Will Learn?
This course covers everything from Python fundamentals to deploying real machine learning models. Here is a complete breakdown of the curriculum:
Module 1: Python for Data Science
- Python basics — variables, loops, functions, and data structures
- Working with lists, dictionaries, and tuples
- File handling and error management
- Introduction to Jupyter Notebooks
Module 2: Data Manipulation with Pandas & NumPy
- Loading and exploring datasets
- Data cleaning — handling missing values, duplicates, and outliers
- Data transformation and feature engineering
- Merging, grouping, and aggregating data
Module 3: Exploratory Data Analysis (EDA)
- Understanding your data through statistics
- Identifying patterns, correlations, and trends
- Asking the right questions from your data
- Real-world EDA project walkthrough
Module 4: Data Visualization
- Creating charts and graphs with Matplotlib
- Beautiful visualizations with Seaborn
- Storytelling with data — how to present insights visually
- Dashboard-ready plots for reports and presentations
Module 5: Machine Learning with Scikit-Learn
- What is Machine Learning? Supervised vs. Unsupervised Learning
- Linear Regression — predicting continuous values
- Logistic Regression — binary classification problems
- Decision Trees and Random Forest
- K-Nearest Neighbors (KNN) and Support Vector Machines (SVM)
- K-Means Clustering for unsupervised learning
Module 6: Model Evaluation & Optimization
- Train-test split and cross-validation
- Evaluation metrics — accuracy, precision, recall, F1-score
- Overfitting and underfitting — how to fix them
- Hyperparameter tuning with GridSearchCV
Module 7: Real-World Projects
- Project 1: House Price Prediction using Regression
- Project 2: Customer Churn Classification
- Project 3: Sales Data Analysis and Dashboard
- Project 4: End-to-end ML pipeline from raw data to predictions
Tools & Technologies Covered
Python
Jupyter Notebook
Pandas
NumPy
Matplotlib
Seaborn
Scikit-learn
Google Colab
What You Will Gain After Completing This Course?
- Ability to analyze real-world datasets confidently
- Skills to build and evaluate machine learning models from scratch
- A portfolio of 4 real projects to show employers or clients
- Freelancing-ready skills for platforms like Upwork and Fiverr
- Certificate of Completion to add on your LinkedIn and CV
About Your Instructor
Muhammad Hassaan
Muhammad Hassaan is a Data Science and Machine Learning practitioner with hands-on experience as a Marketing Data Analyst at Topline Study and as a Freelance Data Analyst. He completed the Data Science and Machine Learning Using Python certification at LUMS Centre for Continuing Education Studies (January – March 2026), and has worked on real-world data projects involving EDA, predictive modeling, and Python-based analytics solutions.
His teaching approach is practical-first: every concept is taught with real datasets, real problems, and real code — not just theory.
Ready to Start Your Data Science Journey?
Whether you want to land a job, start freelancing, or simply understand the data-driven world around you — this course gives you everything you need. No prior experience required. Just bring curiosity and commitment.