Data Science Bootcamp
Are you an aspiring Data Scientist or Machine Learning & AI Engineer? Our comprehensive Data Science Bootcamp is designed for individuals with a background in technology, mathematics, or related fields. In less than 12 months, you will deepen your expertise in advanced analytics, machine learning, AI fundamentals, and data modeling using Python while gaining hands-on experience with real-world datasets. A foundational understanding of programming and analytical concepts is required for success in this program.
2026 Intakes in Progress
Full-time Hybrid
Start Date:
March 2nd, 2026
Course Duration:
28 Weeks
Mode of Learning:
Online & Physical Classes | Mon - Fri 8 am - 5 pm E.A.T
Tuition Fee:
Ksh 200,000
Brochure:
Full-time Remote
Start Date:
March 2nd, 2026
Course Duration:
28 Weeks
Mode of Learning:
100% Online Classes | Mon - Fri 8 am - 5 pm E.A.T
Tuition Fee:
Ksh 174,000
Brochure:
Part-time Remote
Start Date:
March 2nd, 2026
Course Duration:
37 Weeks
Mode of Learning:
100% Online Classes | Mon - Fri 6pm - 9 pm E.A.T
Tuition Fee:
Ksh 200,000
Brochure:
Acquire in-demand data skills that are transforming businesses and industries today
If you aspire to be a Data Scientist, Data Analyst, or Machine Learning Engineer, this program is perfect for you. Ideal candidates include university graduates and professionals who have prior experience with programming, data analysis, or quantitative problem-solving.
Our comprehensive Data Science course will guide you from beginner to mid-level, covering essential topics such as Python for Data Science, data cleaning, analysis, visualization, and machine learning. You’ll gain hands-on experience through practical projects and receive mentorship from industry experts.
By the end of the program, you’ll be an exceptionally skilled professional, ready to tackle real-world challenges using the power of data!
Course Details
Data Science is an interdisciplinary field that deploys algorithms, and other scientific methods and processes to acquire insights and knowledge from data. Data Scientists are equipped with the knowledge of how to use data, tell a story, and derive insights for businesses. Many industries are now leveraging data for decision-making in their day-to-day operations and forecasting.
- Ideal candidates include university graduates and professionals who have prior experience with programming, data analysis, or quantitative problem-solving.
- Ongoing university student/graduate who has taken a course that has math and statistics concepts and/or IT related related courses.
- Working professionals who work with data e.g fintech, banking, research
- Have a basic understanding or strong background in tech, programming, math & statistics
- Have a university/college education (ongoing or graduated).
- Complete the application process by taking a technical assessment test
- Have a laptop with the following specs (core i5, 8GB RAM, 500GB storage).
- Have stable internet access
- In-demand Skill Set: Data science is at the forefront of the digital age. As businesses increasingly rely on data for decision-making, professionals with data science skills are in high demand across various industries.
- Career Opportunities: Learning data science opens up a wide array of career opportunities, ranging from data analyst and machine learning engineer to data scientist and AI specialist
- Innovation: Whether in healthcare, finance, marketing, or other fields, data science plays a pivotal role in driving innovation and creating new possibilities.
- High Earning Potential: Data scientists are often among the top earners in the technology sector.
- Global Impact: Data science has the potential to address global challenges, such as healthcare optimization, climate change analysis, and more. By learning data science, you can contribute to solving critical issues on a global scale.
If you are in search of a unique learning experience this is the place for you. We guarantee you will learn market-aligned skills through our practical and comprehensive curriculum.
- Project-based learning
- Access to large data sets & real-world business case studies
- Technical Mentor Support & Live instructor classes
- 12-month graduate support
- Job placement support
Dive into the fast-growing world of data science and take your career to the next level.
Get StartedCurriculum Overview
- Onboarding week
- Course Overview
- Accounts setup
- Tools, system configurations, and installations
- Learn how to develop professional soft skills
- Learn how to build your professional brand with a standout resume, LinkedIn profile, and portfolio
- Resume + portfolio skeleton review
- Learn the fundamentals of programming for data science, including control flow, loops, functions, and core data structures. You’ll also gain hands-on experience with file handling and logging, ending the module with a summative assessment to reinforce practical application.
- Introduction to Data Science: Explore the foundations of data science, from understanding different data types and data collection to applying statistical analysis and visualizations using Python. You’ll work with Pandas and Seaborn for data analysis, learn object-oriented programming concepts, and complete summative assessments to validate your understanding.
- Introduction to SQL: Develop essential database skills by learning how to work with SQL for data retrieval, analysis, and data modeling. You’ll practice filtering, grouping, and joining data, analyze datasets using SQL and Pandas, and gain exposure to database design and the data engineering lifecycle, culminating in a summative assessment.
- Cloud Computing, Generative AI & Dashboards: Learn how to work with big data and cloud-based analytics using PySpark and Python, alongside NumPy and Pandas. You’ll build dashboards for data analysis and visualization, explore Generative AI applications in data science, and apply advanced visualization workflows, culminating in a summative assessment.
- Inferential Statistics: Develop a strong understanding of probability, distributions, and statistical inference. You’ll apply hypothesis testing, A/B testing, and inference techniques for means, proportions, and categorical data, while learning when to use parametric versus non-parametric methods. The module concludes with a summative assessment.
- Regression: Master regression techniques used in real-world data science, from linear and multiple regression to logistic regression. You’ll learn model fitting, statistical inference, regularization, and model selection methods, reinforced through practical exercises and summative assessments.
- Prepare to land your dream Data Scientist role through targeted interview coaching.
- Practice technical and behavioral questions to refine your portfolio and gain confidence through mock interviews and personalized feedback.
- Mock interviews
- Introduction to Machine Learning: Understand the foundations of machine learning through statistical learning theory, the bias–variance tradeoff, and supervised learning techniques. You’ll build and evaluate models such as logistic regression, decision trees, ensemble methods, and support vector machines, while learning model tuning, evaluation metrics, and end-to-end machine learning pipelines. The module concludes with a summative assessment.
- Machine Learning with Scikit-Learn: Apply machine learning concepts using Scikit-Learn to solve real-world problems. You’ll work with distance-based models like k-nearest neighbors, dimensionality reduction with PCA, clustering and Gaussian mixture models, and recommendation systems, including market segmentation use cases. A summative assessment validates your practical skills.
- NLP, Time Series & Neural Networks: Understand the fundamentals of working with text, sequential, and structured data. You’ll explore Natural Language Processing (NLP), model text data, analyze and model time series, and build neural networks including multi-layer perceptrons. The module also covers deep learning fundamentals, preparing you for practical, real-world applications. A summative assessment concludes the module.
- Neural Networks & Similar Models: Advance your deep learning skills with techniques such as normalization and regularization. Learn Convolutional Neural Networks (CNNs) for computer vision, Recurrent Neural Networks (RNNs) and attention mechanisms for sequence modeling, Transformers, and Generative AI. Hands-on projects reinforce learning, with a summative assessment validating your practical mastery.
- Technical Assessment Test Week
- Data Science Final Project
Learning data science opens the door to a fulfilling and dynamic career, enabling you to leverage data to drive innovation and solve real-world problems.
Career opportunities
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Data Engineer
- AI Research Scientist
- Big Data Engineer/Architect
- Product Analyst
Analyze complex data sets to discover patterns, build predictive models, and drive business decisions using machine learning and statistical methods.
Collect, process, and perform statistical analysis on data to help organizations make informed decisions, often focusing on reporting and visualization.
Design, develop, and deploy machine learning models and algorithms that can automate tasks and make predictions from data.
Build and maintain the infrastructure and architecture for data generation, ensuring that data is accessible and well-organized for analysis.
Develop new algorithms and models in artificial intelligence and machine learning, pushing the boundaries of what’s possible with data-driven technologies.
Design and manage large-scale data processing systems to handle massive data sets, typically using technologies like Hadoop, Spark, or cloud services.
Analyze product usage data to help companies improve their products and customer experience based on user behavior and feedback.
Ready to take a step in transforming your career?
