Name: Master Python & ML: Stats, Analysis & Data Visualization
Availability: InStock
Rating: 4.4 (1,629 students reviews)

Course Title: Master Python & ML: Stats, Analysis & Data Visualization
Instructor: Muhammad Shafiq (Data Scientist | AI & ML Engineer | Lecturer | Researcher)
Target Audience:
- Beginners with no prior coding or data science experience
- Professionals seeking career transition into data science or machine learning
- Analysts aiming to enhance skills in Python, statistics, and data visualization
- Students or researchers needing practical data analysis and ML training
Prerequisites: None (covers fundamentals to advanced topics)

Key Topics Covered:
- Python Programming (syntax, data structures, functions, OOP)
- Data Manipulation with Pandas and NumPy
- Statistics & Probability for data science and machine learning
- Machine Learning Algorithms:
  - Linear & Logistic Regression
  - Decision Trees & Random Forests
  - K-Means Clustering
  - Model evaluation and optimization
- SQL for Data Extraction (ETL processes)
- Data Visualization with:
  - Matplotlib & Seaborn (Python libraries)
  - Tableau (dashboard creation)
- Real-World Projects (portfolio-building case studies)
Key Skills Learned:
- Proficiency in Python for data analysis and automation
- Statistical reasoning for hypothesis testing and data interpretation
- Building, training, and deploying ML models
- SQL querying for database management
- Creating interactive visualizations and dashboards
- End-to-end data science project execution

Duration:
- Video Content: ~30 hours (self-paced)
- Practice Tests: 3 included
- Lectures: 100+ (structured modules)
Format:
- Self-paced online course (lifetime access)
- Mobile & desktop compatible
- Hands-on coding exercises and quizzes
Resources:
- Downloadable Jupyter Notebooks and datasets
- Cheat sheets for Python, Pandas, and SQL
- Project templates for portfolio development
- Q&A support from instructor