Data Science Full-time Online Course

Future Proof Your Career with Market-Relevant Skills in Data Science. Master Data Analysis, Python, Machine Learning, and AI in 25 weeks
Data Science Full-time Online Course

Secure the future of your career by joining our 25-week Data Science Online Course. Learn in-demand Data Skills that are reshaping businesses and industries today!

If you are an aspiring Data Scientist, Data Analyst or Machine Learning Engineer this is the right program for you. Stay ahead of the curve with our world-class curriculum crafted in partnership with Flat Iron School [ renowned US-based Tech Bootcamp].

Our comprehensive Data Science course will move you from beginner to mid-level. In 25 weeks you will learn Python for Data Science, Data cleaning, analysis, visualization, machine learning and so much more through practical hands-on projects and mentorship from industry experts.

At the end of the program, you will be an exceptionally skilled professional, ready to apply your knowledge to solve real-world challenges through the power of data.

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, analysts, and anyone eager to harness the power of data to drive decisions. This program is for you if you want to work with Data to:

  1. Help businesses leverage data for innovation and success
  2. Innovate and predict future trends in business and other industries
  3. Learn how to analyze data, and provide data-driven insights to make decisions
  4. Elevate their careers or switch to Data Science within a year

  • 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 upwards, 8GB RAM, 500GB upwards of storage).
  • Have stable internet access

  1. In-demand Skillset: 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.
  2. 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
  3. Innovation: Whether in healthcare, finance, marketing, or other fields, data science plays a pivotal role in driving innovation and creating new possibilities.
  4. High Earning Potential: Data scientists are often among the top earners in the technology sector.
  5. 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

  • Students will engage in 40 hours of online learning weekly from Mon – Friday for a total of 25 weeks.
  • Students attend live lectures & daily stand ups
  • Classes are online or hybrid depending on your preference
  • Additional classes & helpdesk support are available

Become a Hot Asset in the most in-demand career pathways in tech of the 21st century

Course Details

Find out the pacing options available, price, and more information about this Data Science Course at Moringa.

Curriculum Developed by:

Flatiron School


25 weeks


Online | Mon to Fri from 8am – 5pm

Tuition Fees:

Ksh 174,000 ( USD 1740 )
Download fees installment plans on the Data Science Full-time fees installation plans document

Course Prerequisites

To become a data scientist, you will need some understanding of Software Engineering fundamentals, Statistics, and the ability to apply all the knowledge in new and dynamic domains.

All applicants need to meet the criteria outlined below to gain admission and succeed in the 25 weeks program:-

  1. All applicants must be 18 years and above and provide proof of ID/Passport
  2. Have a basic understanding or strong background in math & statistics concepts.
  3. Have a university/college education (ongoing students or graduates are more likely to join).
  4. All applicants are required to complete the application process by taking a technical assessment test and pass.
  5. Have a laptop with the following specs (core i5 upwards, 8GB RAM, 500GB upwards of storage).
  6. Have stable internet access.
  7. Students are required to be available for the full-time course from Mon-Fri and be present in at least 90% of the class sessions.

Moringa Data Science Curriculum

Our Data Science course will teach you the technical and soft skills that will have you adapt faster, learn how to learn, and stay relevant in the industry for a long time.

Discover our Data Science Modules

Orientation, Pre Work and Introduction to Data Science Principles

During orientation, you learn more about Moringa, our policies, learning model, learning platform, classroom structure, and learning schedule.

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 with your coursemates.

You will also learn about Dat Science Principles, and Software Engineering principles and dive deep into python programming.

Data Analysis & Engineering

In this phase, students will be introduced to fundamentals of python for Data Science. You’ll learn how to use Jupyter Notebooks, and will be familiarized with popular Python libraries that are used in data science such as Numpy and Pandas. To organize your data, you’ll learn about data structures, relational databases, ways to retrieve data, and the fundamentals of SQL for data querying structured databases. Furthermore, you will learn how to access data from various sources using API’s and perform Web scraping.

At the end of this phase, students will be able to use skills to collect, organize and visualize data with the goal of providing actionable insights.

Students will go through training with our professional development trainers in Leading self and working with others.

Scientific Computing & Quantitative Methods

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.

Students will go through training with our professional development trainers in Communicating for Impact & Entrepreneurial Thinking.

Machine Learning Fundamentals

In this phase, students learn about machine learning with a heavy focus on supervised learning. For starters, learners get into regression analysis and a new form of regression — logistic regression. In building regression models, students also learn penalization terms, preventing overfitting through regularization, and using cross-validation to validate regression models.

At the end of this phase, students will be able to build and implement the most important machine learning techniques.

Students get a 1 week break to relax and boost energies to complete the remaining modules.

Students will go through training with our professional development trainers in Project Management and Career Readiness.

Advanced Machine Learning

This phase of the course focuses on a variety of Data Science techniques. Students learn about unsupervised learning techniques like clustering and dimensionality reduction. Students will be introduced to threading and multiprocessing to be able to work with big data. In doing so, you’ll learn about PySpark and AWS, and how to use those tools to build a recommendation system. You’ll also learn about deep learning, neural networks and how to perform sentiment analysis.

Final Data Science Projects

In your final project, learners work individually or in groups to apply the technical and soft skills training and knowledge. Students will be required to create a large-scale data science and/or machine learning project. This final project provides an in-depth opportunity for you to demonstrate your learning accomplishments and get a feel for what working on a large-scale data science project is really like.

Career opportunities for our Data Science Graduates

Ready to take a step in transforming your career?