Data Science Bootcamp
An intensive Data Science Bootcamp for those looking to upskill or launch a career in Data Science. Master Data Analytics, Python, Machine Learning and AI.
2025 Intakes in Progress
Full-time Remote
Start Date:
February 3rd, 2025
Course Duration:
26 Weeks
Mode of Learning:
100% Online Classes | Mon - Fri 8 am - 5 pm E.A.T
Tuition Fee:
Ksh 174,000
Full-time Hybrid
Start Date:
February 3rd, 2025
Course Duration:
26 Weeks
Mode of Learning:
Online & Physical Classes | Mon - Fri 8 am - 5 pm E.A.T
Tuition Fee:
Ksh 200,000
Part-time Remote
Start Date:
February 3rd, 2025
Course Duration:
36 Weeks
Mode of Learning:
100% Online Classes | Mon - Fri 6pm - 9 pm E.A.T, Saturday 9am - 1pm
Tuition Fee:
Ksh 200,000
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.
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.
- Aspiring data scientists and data analysts who are eager to harness the power of data to drive decisions.
- 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 math & statistics concepts.
- 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
- Course Overview
- System configurations and installations
- Onboarding
The Data Science pre-work covers introductory Data Science concepts. By the end of pre-work, you will be prepared to dive into the course material and you will be at the same level as your coursemates. You will also learn about Data Science Principle and dive deep into python programming.
In this phase, students will learn the fundamentals of Python for Data Science, including the use of Jupyter Notebooks and key libraries like Numpy and Pandas. They’ll explore data structures, relational databases, and SQL for querying structured databases, while also gaining skills in accessing data via APIs and web scraping. By the end, students will be able to collect, organize, and visualize data to deliver actionable insights.
In phase 2, students learn about the fundamentals of probability theory like combinations and permutations. They also learn about statistical distributions and how to create samples, then apply this knowledge by running A/B experiments. At the end of this phase, students will be able to build their first data science model using linear regression.
In this phase, students dive into machine learning with a strong focus on supervised learning. They begin with regression analysis, including logistic regression, and learn key techniques such as regularization to prevent overfitting and cross-validation for model validation. By the end, students will be able to build and implement essential machine learning techniques effectively.
This phase of the course explores various Data Science techniques, focusing on unsupervised learning methods such as clustering and dimensionality reduction. Students will be introduced to threading and multiprocessing to handle big data, learn to use tools like PySpark and AWS to build recommendation systems. Additionally, they will delve into deep learning and neural networks, gaining skills in performing sentiment analysis.
In the final project, learners will work individually or in groups to apply their technical and soft skills in a comprehensive data science or machine learning project. This project offers an in-depth opportunity to showcase their learning achievements and experience the process of working on a large-scale data science initiative, allowing students to integrate their knowledge and demonstrate their capabilities in a practical setting.
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?
