Psalm E. Obiri - Tech Expert, Web developer & Instructor

Course Overview

This comprehensive course is designed for developers and professionals worldwide looking to master data science skills. You'll learn through practical, real-world projects that are relevant to global market needs.

Global Perspective/Requirements

Anyone can take this course (no prior knowledge of data science is needed

Direct Support

Get personalized guidance from an experienced instructor

What You'll Learn

Data analysis with Pandas

Data visualization with Matplotlib

Statistical analysis

Machine learning basics

Data cleaning and preprocessing

Real-world data projects

Psalm Obiri

Full Stack Developer & Tech Instructor

1000+ Students

5+ Years Experience

4.8 Rating

Experienced developer and instructor with a passion for teaching technology skills to students worldwide. My courses focus on practical, market-relevant skills that you can apply immediately.

Course Curriculum

Python for Data Science

Learn Python libraries for data analysis

8 lectures 6 hours

Lecture 1: Python for Data Science Part 1 0.8h

Lecture 2: Python for Data Science Part 2 0.8h

Lecture 3: Python for Data Science Part 3 0.8h

Lecture 4: Python for Data Science Part 4 0.8h

Lecture 5: Python for Data Science Part 5 0.8h

Lecture 6: Python for Data Science Part 6 0.8h

Lecture 7: Python for Data Science Part 7 0.8h

Lecture 8: Python for Data Science Part 8 0.8h

Data Analysis with Pandas

Master data manipulation and analysis

10 lectures 8 hours

Lecture 1: Data Analysis with Pandas Part 1 0.8h

Lecture 2: Data Analysis with Pandas Part 2 0.8h

Lecture 3: Data Analysis with Pandas Part 3 0.8h

Lecture 4: Data Analysis with Pandas Part 4 0.8h

Lecture 5: Data Analysis with Pandas Part 5 0.8h

Lecture 6: Data Analysis with Pandas Part 6 0.8h

Lecture 7: Data Analysis with Pandas Part 7 0.8h

Lecture 8: Data Analysis with Pandas Part 8 0.8h

Lecture 9: Data Analysis with Pandas Part 9 0.8h

Lecture 10: Data Analysis with Pandas Part 10 0.8h

Data Visualization

Create insightful charts and graphs

8 lectures 6 hours

Lecture 1: Data Visualization Part 1 0.8h

Lecture 2: Data Visualization Part 2 0.8h

Lecture 3: Data Visualization Part 3 0.8h

Lecture 4: Data Visualization Part 4 0.8h

Lecture 5: Data Visualization Part 5 0.8h

Lecture 6: Data Visualization Part 6 0.8h

Lecture 7: Data Visualization Part 7 0.8h

Lecture 8: Data Visualization Part 8 0.8h

Statistical Analysis

Apply statistical methods to data

7 lectures 5 hours

Lecture 1: Statistical Analysis Part 1 0.7h

Lecture 2: Statistical Analysis Part 2 0.7h

Lecture 3: Statistical Analysis Part 3 0.7h

Lecture 4: Statistical Analysis Part 4 0.7h

Lecture 5: Statistical Analysis Part 5 0.7h

Lecture 6: Statistical Analysis Part 6 0.7h

Lecture 7: Statistical Analysis Part 7 0.7h

Machine Learning

Build basic machine learning models

8 lectures 7 hours

Lecture 1: Machine Learning Part 1 0.9h

Lecture 2: Machine Learning Part 2 0.9h

Lecture 3: Machine Learning Part 3 0.9h

Lecture 4: Machine Learning Part 4 0.9h

Lecture 5: Machine Learning Part 5 0.9h

Lecture 6: Machine Learning Part 6 0.9h

Lecture 7: Machine Learning Part 7 0.9h

Lecture 8: Machine Learning Part 8 0.9h

Capstone Project

Complete a real-world data science project

4 lectures 4 hours

Lecture 1: Capstone Project Part 1 1h

Lecture 2: Capstone Project Part 2 1h

Lecture 3: Capstone Project Part 3 1h

Lecture 4: Capstone Project Part 4 1h

Data Science with Python