DAT
Beginner
Data Science
Pandas and NumPy Essentials
Master Pandas and NumPy Essentials with this in-depth training program designed for the African tech community. Whether you're just starting out or looking to level up your skills, this course provides everything you need.\\n\\nYou'll work on practical exercises that mirror real-world challenges faced by developers and tech professionals. Our step-by-step approach ensures you understand not just the 'how' but also the 'why'.\\n\\nJoin thousands of students who have transformed their careers through our courses.
Course Syllabus
Week 1: Introduction & Setup
- Lesson 1: Working with Visualization Preview 14min
- Lesson 2: Mastering Cleaning Preview 13min
- Lesson 3: Understanding Statistical Analysis 11min
Week 2: Core Concepts
- Lesson 1: Building Visualization 19min
- Lesson 2: Advanced Cleaning Techniques 19min
- Lesson 3: Visualization Fundamentals 9min
- Lesson 4: Cleaning Fundamentals 19min
- Lesson 5: Working with Cleaning 16min
Week 3: Hands-On Practice
- Lesson 1: Mastering Visualization 19min
- Lesson 2: DataFrames Best Practices 15min
- Lesson 3: Advanced Statistical Analysis Techniques 17min
- Lesson 4: Deep Dive into DataFrames 20min
- Lesson 5: Advanced Statistical Analysis Techniques 22min
- Lesson 6: Understanding Statistical Analysis 21min
Week 4: Intermediate Techniques
- Lesson 1: Introduction to Cleaning 24min
- Lesson 2: Deep Dive into Statistical Analysis 22min
- Lesson 3: Mastering ETL 9min
- Lesson 4: ETL Fundamentals 12min
- Lesson 5: Building Cleaning 8min
Week 5: Advanced Topics
- Lesson 1: Introduction to Visualization 21min
- Lesson 2: Working with Visualization 14min
- Lesson 3: Understanding Cleaning 25min
Week 6: Real-World Projects
- Lesson 1: Visualization Best Practices 13min
- Lesson 2: ETL Explained 25min
- Lesson 3: ETL Explained 20min
- Lesson 4: DataFrames Explained 13min
Week 7: Best Practices
- Lesson 1: Visualization Fundamentals 9min
- Lesson 2: Working with DataFrames 15min
- Lesson 3: Practical Cleaning 8min
- Lesson 4: Deep Dive into DataFrames 21min
- Lesson 5: Working with Statistical Analysis 17min