Python Data Analysis Course

Master data science tools in Python for practical data analysis and scientific computing

What is data analysis?

Data analysis is the process of extracting meaningful insights from data through inspection, cleansing, transformation, and modeling. It involves using tools and techniques to understand patterns, trends, and relationships in data to support decision-making and problem-solving.

Why should I learn Python for data analysis?

Python is the leading language for data science and analysis because it has a rich ecosystem of libraries (Pandas, NumPy, Matplotlib), is easy to learn and use, has strong community support, and is used by major companies worldwide. Learning Python for data analysis opens doors to lucrative careers in data science, analytics, and machine learning.

Who is this course suitable for?

This course is ideal for Python programmers who want to learn data analysis, analysts seeking to leverage Python, web developers expanding into data-driven applications, and professionals from any field with prior Python experience who want to gain data science skills.

Do I need prior Python experience?

Yes, you should have solid Python programming knowledge at least equivalent to our Web Programming Bootcamp. This course assumes you're comfortable with Python basics and focuses on data analysis-specific tools and techniques.

What are the prerequisites?

• Completion of or equivalent experience to our Web Programming Bootcamp
• Solid understanding of Python programming fundamentals
• Comfortable working with command line/terminal
• A modern laptop with at least 8GB RAM
• Stable internet connection (10 Mbps minimum)

What tools and libraries will I learn?

You'll master the core data analysis stack: Pandas for data manipulation, NumPy for numerical computing, Matplotlib for visualization, Jupyter for interactive analysis, and introduction to Scikit-learn for machine learning. You'll also learn IPython, Python file handling, and statistical analysis tools.

Is this a hands-on course?

Absolutely! This is a practical, project-based course with extensive hands-on exercises. You'll work through real-world data analysis examples, clean and prepare actual datasets, create visualizations, and solve practical data analysis problems throughout the course.

Will I receive a certificate?

• Attendance Certificate: If you attend 80% of sessions and complete all classwork
• Competency Certificate: If you also successfully complete the practical data analysis projects

What learning materials are provided?

We provide comprehensive electronic course materials, Jupyter notebooks with examples, datasets for practice, and access to a structured learning portal. You'll have access to all materials even after the course completes for continued learning.

Can I access course content after completion?

Yes, your login and access to all course materials remain active for as long as you need. We'll check with you periodically to ensure you no longer need access before removing it.

What career opportunities follow this course?

• Data Analyst
• Junior Data Scientist
• Business Analyst
• Data Engineer
• Analytics Developer
• Further study in advanced data science and machine learning courses

How does this course compare to other data science courses?

This course is practical and immediately applicable, focusing on real-world data analysis problems with hands-on examples. It builds on your existing Python knowledge and equips you with industry-standard tools used by professional data analysts. The curriculum covers both fundamentals and advanced techniques.

Python Data Analysis Course

R14 995

• Duration: 40 hours
• Skill Level: Intermediate
• Format: Full-time or Part-time options
• Language: English
• Updated: 7 January 2026
• Financing: Flexible student loan options available