Overview

Become a Data Scientist with our immersive core program

Data Science is revolutionising industries by turning vast amounts of data into actionable insights and strategic decisions. As businesses and organisations increasingly rely on data to drive their operations and growth, the demand for skilled data scientists continues to soar. Learning Data Science equips you with the ability to analyze complex datasets, build predictive models, and uncover hidden patterns that can transform business strategies, enhance customer experiences, and foster innovation. A career in Data Science not only offers lucrative opportunities but also places you at the forefront of technological advancements and problem-solving.

Zindua’s Data Science Core Program is designed to provide a comprehensive education in the field, covering both foundational and advanced topics. Starting with essential skills in Python Programming, Data Analysis, SQL, Advanced Excel, and BI Tools, the program ensures a strong grounding in data analytics. Building on this foundation, you will delve deeper into Machine Learning, exploring algorithms, model evaluation, and feature engineering. The curriculum includes hands-on projects, real-world case studies, and practical applications, ensuring you gain the expertise needed to handle complex data challenges. By the end of the program, you will be proficient in using data science tools and techniques to solve real-world problems and drive business value.

This program is perfect for aspiring data scientists, data analysts looking to advance their skills, and professionals aiming to transition into the field of data science. It is suitable for individuals with a passion for data, analytical thinking, and a desire to leverage data for impactful decision-making. While no prior experience in data science is required, a basic understanding of mathematics and statistics is necessary. Whether you’re a recent graduate, a professional seeking to upskill, or an entrepreneur wanting to harness the power of data, Zindua’s Data Science Core Program will equip you with the knowledge and skills to excel in the dynamic and rapidly evolving field of data science.

Choose the learning schedule that best works for you

Full-time schedule

Ideal for learners without other work or school commitments.

  • Graduate in 4 months
  • 35-40-hour weekly commitment
  • In-person classes on 3 weekdays; live online classes on 2 weekdays
  • Classes from 9am – 2pm with take-home daily challenges and weekend practice projects
  • Cohort intakes every 2 months
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Part-time schedule

Ideal for learners with additional work or school commitments.

  • Graduate in 7 months
  • 20-25-hour weekly commitment
  • Online classes on Monday to Thursday evenings from 7pm – 9pm with daily challenges
  • In-person classes on Saturdays from 10am to 2pm with weekly projects afterwards
  • Cohort intakes every 5 weeks
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In-person classes based at our Westlands/Lavington Office in Nairobi. Other cities from 2025.

Curriculum

What you’ll learn in our Data Science Program

Curated from our in-depth research and experience of the most in-demand skills for data science career pathways, our curriculum is broken down into 5 modules encompassing the following:

Learn the fundamentals of programming with the Python programming language. By the end of the module, you should have an apt understanding of building scripts with Python, interacting with databases, and sourcing data through APIs and scraping.

  • Dev Foundations: Git version control, Linux, and CLI/Terminal foundations
  • Python Basics: variables, conditional statements, loops, and functions
  • Data Types: strings, lists, files, tuples, sets, and dictionaries
  • Using Web Services: regular expressions, web scraping, and APIs
  • Advanced Python: object-oriented programming, unit-testing, and working with databases

Learn the essential Python libraries for data analysis. By the end of module, you’ll be able to clean data, analyse, visualise, and even deploy dashboards using Python data libraries.

  • Numpy Arrays: Learn how to do fast vectorised data operations with the Numpy library
  • Pandas Tabular Data: Learn how analyse and manipulate data with the Pandas library
  • Data Visualisation: Visualise data with plots built by Matplotlib and Seaborn libraries
  • Advanced Visualisation: Build geographic plots with GeoPandas and interactive plots with Plotly
  • Deployment of Dashboards: Deploy dashboards with a coherent data story with Dash by Plotly

Learn the fundamentals of data analytics outside the Python program ming environment. By the end of the module, you’ll be able to query SQL relational databases, design & build databases, and build dashboardsa with BI tools.

  • SQL Programming: Build basic and advanced queries with SQL on relational databases
  • SQL Database Design: Learn how to design databases, build, and optimise relational databases
  • Advanced Excel: Learn advanced formulae, Excel statistical modelling, build charts, forecasts, and pivot tables
  • Tableau Visualisation: Data storytelling through live dashboards with Tableau business intelligence tool

Learn the fundamentals of machine learning with Scikit Learn. By the end of the module, you’ll be able to preprocess data for machine learning, do supervised learning problems (regression and classification), and evaluate your model while optimising model performance.

  • Data Preprocessing: Learn the essential steps for preprocessing data for machine learning models
  • Regression: Learn linear regression, adding variance to models, regularisation, and generalised estimators
  • Classification: Learn algorithms such as logistic regression, KNN, Naive Bayes, SVM, trees, and ensemble methods
  • Model Evaluation: Learn how to evaluate model performance, hyperparameter tuning, and error analysis

Learn advanced machine learning concepts such as unsupervised learning, time series analysis, and deep learning. By the end of the module, you’ll be able to solve machine learning problems beyond your typical supervised learning prediction problems.

  • Feature engineering: Learn dimensionality reduction and feature selection processes
  • Clustering & Anomalies: Learn algorithms for clustering as well as outlier handling & anomaly detection
  • Time Series Analysis: Learn statistical models for handling time series problems with stats models
  • Deep Learning: Explore the foundations of neural networks, text processing, and computer vision

All Zindua programs require students to be versed with computer programming fundamentals for building efficient code and scalable solutions. In this program, here are the essential data structures and algorithms you’ll learn:

  • Basic Algorithms: Learn the Big-O Notation, Search, and Sorting Algorithms
  • Linear Data Structures: Learn Arrays, Hash maps, Stacks, Queues, Linked Lists, Trees, and Graphs
  • Non-Linear Data Structures: Trees, Graphs, and common algorithms involving trees/graphs such as pathfinding
  • Advanced Algorithms: Learn divide and conquer algorithms i.e. dynamic programming and greedy algorithms
  • Databases & Cloud: Learn how to optimise databases and how to deploy machine learning apps on AWS/Azure

To graduate the program, a student will be required to complete an end-to-end data science project involving sourcing data, cleaning and preprocessing, and modelling data for predictions using the machine learning techniques learned in the program. Students have freedom to choose project on an industry niche of their interest or one that is aligned with their domain knowledge.

Zindua your career in tech. Join our Data Science program today!

Apply Now

Testimonial

Hear from a graduate

Mercy Samoei, data science program graduate in 2023

If I compare the person I am now, versus the person I was prior to joining Zindua, I would say that I have grown in more than one aspect. Zindua has been a good learning experience: amazing tutors, the students you get to interact with, and it is also quite time friendly. Classes are usually sizeable enough so it is easy to have a one-on-one experience, not like the normal classroom experience you get from uni. What I love most about Zindua is the personalised learning approach, blended learning, where some classes are online and others in-person. They also have a very favourable income-share agreement financing.

Mercy Samoei, Data Science Graduate

Your Zindua experience runs from admissions to placement

1

Complete application

Takes less than 2 minutes to complete. Choose your program and expected start date.

2

15-minute interview

The interview allows us to make sure your background aligns with your chosen program.

3

Pay enrolment deposit

Confirm your enrolment by paying a KES 5K deposit, deductible from your actual fees.

1

Personalised Learning

We pride ourselves in very small classes, allowing you as much touch with your technical mentor.

2

Project-based approach

You’ll work on a short daily challenge on weekdays, weekly project, and capstone after each module.

3

Global cloud certification

Curriculums are modelled on certification exams by Microsoft Azure and AWS.

1

Career Development

Beyond classes, we have a module focused on CVs, LinkedIn, portfolios, and technical interviews.

2

Job Placement Support

We don’t offer job guarantees but we connect some of our graduates to our employer networks.

3

Life-long engament

As an alumni, you’ll have free access to our masterclasses and placement support on a need-basis.

Zindua your career in tech. Join our Data Science program today!

Apply Now

financing

Choose the pricing options that fits your needs

We champion flexible financing options to improve the accessibility of our programs:

One-time Upfront Payment

Pay KES 120K all one-time fee (20% cheaper than instalment payments)

Pay in TWO Quarterly Instalments

Pay KES 62.5K twice with 3-month gap between the payments.

Pay in FIVE Monthly Instalments

Pay KES 30,000 for every month for 5 monthly instalments

Flexi Payment Plan (Lipa mdogo mdogo)

Pay KES 13,750 monthly for 12 months. This financing will require the student/parent (whoever will be making payments) to go through a credit vetting process by Chaptr Global. This option is ideal for students who are not eligible for an income-share agreement but still cannot afford the standard pricing plans.

Income-Share Agreement (Learn now, pay later)

Pay 50% of tuition fees and defer the rest into an income-share agreement. You’ll pay KES 15K (instead of KES 30K) for every 5-week module for 5 total instalments. Once you graduate, you’ll be required to pay 10% of your earned income for 24 months. If you do not get a job you pay nothing! This financing plan is ONLY available to students with Bachelor’s Degree or in their final year of university i.e. students who’ll be looking for employment immediately they graduate Zindua School.

Frequently asked questions

We have a three-step admissions process. Apply on website, attend a 15-minute interview, and pay the enrolment deposit to confirm your enrolment. Simple and straightforward. Since there could be some weeks between the time you pay the deposit and the orientation program, you’ll be invited to our Free Courses to start learning concepts that would be beneficial for your learning journey.

Yes, Zindua School has an enrolment deposit of KES 5,000 which is deductible from your program fees. The deposit allows us to confirm your slot in an upcoming intake. Fees will be paid (minus the deposit) once you have started the program.

Zindua School is extremely practical and our focus is on preparing our students for real-world problems in today’s job market. Most of our graduates get hired on the basis of their portfolio and this speaks to the quality of the skills you’ll gain at Zindua School.

Unfortunately, we do NOT offer a job guarantee. However, we do offer job placement support for graduates. This involves our career module where you’ll optimise your CV/resume, LinkedIn profile, portfolio, and even learn about technical interviews. Additionally, we do connect some of our graduates to our constantly growing employer networks.

For our full-time program, you’ll be expected to attend classes in-person on three weekdays and online on two weekdays. Classes run from 9am to 2pm, with take home coding assignments on each day. You are required to commit 35-40 hours weekly if you plan to join us full-time.

For our part-time program, you’ll be expected to attend online classes in the evening from Monday to Thursday. The online classes run for two hours and are slotted anytime from 6pm to 10pm based on your class group. You’ll have in-person classes on Saturdays from 10am to 2pm. You are required to commit 20-25 hours weekly to cover for class sessions and out-of-class projects. This is ideal for those with work or school commitments.

Note: full-time programs are shorter than the part-time program as there is more time committed per week for learning. However, both programs cover the same content and have the same expected outcomes.

Our ISA allows you to pay 50% of the program and pay the rest once you start earning through an income-share. When you are not earning, you pay nothing.This financing plan is only open to learners who are in their final year of university or already have a diploma or Bachelor’s Degree. This financing plan only applies to our core programs and specialisation programs; NOT lite core programs (Data Analytics and Web Development) or our short courses (Product Management and Data Structures Algorithms)