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Python for Data Science
NumPy Masterclass
Everything you need to use NumPy with confidence
By Suresh Iyer
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Advanced
English
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What you'll learn
- Understand the core concepts of NumPy and how they fit together
- Build hands-on projects using NumPy that you can add to your portfolio
- Apply NumPy to solve real, practical problems in Data Science & AI
- Follow industry best practices and avoid common NumPy mistakes
- Gain the confidence to use NumPy at work and in interviews
Skills you'll gain
NumPy
Practical Projects
Debugging
Best Practices
Problem Solving
Python for Data Science
About this course
Learn NumPy the practical way. This Data Science & AI course focuses on doing: you'll work through real examples in Python for Data Science, understand the why behind each technique, and finish with projects for your portfolio. Suresh Iyer keeps things clear and example-led, so you build genuine, transferable skill. By the end you'll be ready to use NumPy confidently at work and in interviews.
Curriculum
Getting Started
- Welcome and what you'll build video · 17:00 ▶ Free preview
- NumPy in 10 minutes video · 06:00 ▶ Free preview
- Your first NumPy walkthrough video · 07:00
- Hands-on exercise video · 08:00
- Building the project — part 2 video · 09:00
Core Concepts
- Hands-on exercise video · 12:00
- Building the project — part 2 video · 13:00
- Best practices from industry video · 14:00
Hands-On Practice
- Best practices from industry video · 07:00
- A real-world case study video · 08:00
- Recap and where to go next video · 09:00
- Setting up your environment video · 10:00
Building Real Projects
- Welcome and what you'll build video · 14:00
- NumPy in 10 minutes video · 15:00
- Your first NumPy walkthrough video · 16:00
- Hands-on exercise video · 17:00
- Building the project — part 2 video · 06:00
Going Deeper
- Hands-on exercise video · 09:00
- Building the project — part 2 video · 10:00
- Best practices from industry video · 11:00
Best Practices
- Best practices from industry video · 16:00
- A real-world case study video · 17:00
- Recap and where to go next video · 06:00
- Setting up your environment video · 07:00