Kenya’s digital economy is expanding, yet the demand for skilled data professionals outpaces supply. This 5-week Online Data Science Bootcamp is designed to equip IT professionals, university students, and industry practitioners with practical, industry-relevant data science skills.
Delivered through WordPress LMS named Doable the course provides an engaging, interactive learning experience with:
✅ Hands-on Python programming & data analysis
✅ Real-world projects in agriculture, healthcare, and finance
✅ Machine Learning & Deep Learning fundamentals
✅ Peer collaboration, automated assessments & expert mentorship
Learners will work on projects using Kaggle datasets, Jupyter Notebooks, and Google Colab, gaining practical exposure to data-driven problem-solving. By the end of this bootcamp, participants will develop job-ready skills, increase employability, and contribute to Kenya’s data revolution.
Paul Lemaron is a seasoned data scientist, analyst, and technical trainer with over four years of experience in the tech industry. He has worked with leading companies to develop data-driven solutions and has trained students worldwide in programming and data science. Paul specializes in Python, machine learning, and big data analytics, with a passion for making complex concepts accessible to beginners.
His hands-on, practical teaching approach focuses on real-world applications and experiential learning, ensuring students acquire skills that translate directly into industry demands. He holds a BSc in Computer Science and an MA in Computing in Education from the American University of Beirut (AUB). His experience includes working as a Clinical Data Analyst at Metropolitan Hospital Nairobi, where he utilizes Power BI, Metabase, SQL, Python, and Excel for healthcare data analysis.
Project Title: Bridging the Data Science Skills Gap in Kenya Through an Online Bootcamp
Duration: 5 weeks
Platform: WordPress LMS (Masterstudy) & Articulate Rise 360
Delivery Mode: Fully online, self-paced with interactive modules and real-world projects.
Instruction Design Model: ADDIE Model
Learning Outcomes | ||
Week 1: Master Python basics and set up the development environment. | ||
Week 2: Learn advanced Python concepts and data handling techniques. | ||
Week 3: Perform data analysis and visualization using Numpy, Pandas, Matplotlib, and Seaborn. | ||
Week 4: Apply data analysis skills to real-world projects. | ||
Week 5: Build ML and DL models, complete 5 hands-on projects, and Learn Cloud Computing. | ||