Part-time Data Science Course (Online)

A course for those unable to attend full-time classes but still want to:
➜ Learn Data Science from a reputable institution
➜ Gain practical hands-on training from qualified mentors
➜ Interact with other working professionals in the classroom

Become a Moringa Certified Data Scientist and enjoy up to 12 months of alumni support from our Career Services Department.

33 Weeks of Modelling Data for Analysis, Visualization, & Machine Learning

Course Includes: Python, R, SQL, Pandas, NumPy, Supervised Learning, Advanced Regression, Decision Trees, Neural Networks, and More.

The credits are rolling on a movie you’ve just concluded watching and Netflix automatically queues the preview for another movie that you might like; You’re doing some online shopping on Jumia and while scrolling down the product description, you notice a section that says “Most popular” that has the same product from different vendors at different prices; this is Data Science at work and businesses are always looking for talented individuals to help them analyze and draw actionable insights from their data in order to make informed business decisions. Become a hot asset in one of the most sought-after career pathways of the 21st Century.

Next Intake Dates

August 8th, 2022
Open Apply
November 14th, 2022
Open Apply

Course Prerequisites

To have a good chance of completing and graduating from this course, you will need to:

  • Have a basic understanding of mathematics and statistics concepts.
  • Complete a multiple-choice assessment on probability and statistics to get admission.
  • Have a laptop with these specifications: Core i5 & above, 8GB RAM, and at least 256GB of storage.
  • Have internet access since the classes are online
  • Be available to attend part-time classes running from Monday to Friday 6pm – 9pm.
  • Attend at least 80% of classes and submit project work to graduate successfully.
  • Entry Assessment

    Entry Assessment

    You will need to take a short multiple-choice entry assessment after your application to be admitted to this course.

  • Class Hours

    Class Hours

    • This is a part-time class taking place on weekdays 6pm – 9pm.
    • Students must attend 80% of classes.
    • Learners must check-in with their Technical Mentors at the beginning and end of the lessons.
  • Laptop

    Laptop

    You need a personal laptop with the following minimum specifications: –

    • Core i5 7th gen, 4gb RAM, 256GB Hard Disk.
    • Laptop financing is provided for those who need it.
  • Internet

    Internet

    You need a stable internet connection for live classes, group sessions and to use online resources.

    We support students with internet bundles for online learning. We recommend a good enough, base-level connection.

Data Science remains one of the most exciting fields in Computer Science because it allows practitioners to achieve three significant kinds of results: discovery, insights, and innovation.

Curriculum

Data Science is one of the most highly sought-after jobs due to the abundance of data science career pathways and a lucrative pay scale. We maintain a strong and established connection with key industry figures who help in developing our curriculum in line with industry trends and current demands of the African job market. We aim to ensure learners are best prepared for an ever-evolving industry with the right foundation to find long-term success in their chosen career pathway.

Beginner Module (Prep)
Advanced Module (Core)
Course Overview

Topics covered:

  • Fundamentals of Python programming
  • The Data Science Project Life Cycle
  • Ethics in Data Science
  • Tools: Google Colabs/ Jupyter Notebooks

Topics covered:

  • SQL Programming
  • Project Management with Jira

Tools Used:

  • Python
  • Numpy
  • SQL
  • MySQL
  • Git
  • Github
  • Jira.

Topics covered

  • Data Sourcing & Preparation
  • Data Integrity
  • Data Visualization with Python & Tableau

Topics Covered

  • Descriptive Analysis
  • Sampling Distribution & Time series
  • Hypothesis testing
  • Final Assessment Week

Topics covered

  • Regression
  • Decision Trees
  • KNN
  • Neural Networks
  • Final Assessment Week

Topics Covered

  • Model Performance
  • Dimensionality Reduction
  • Clustering

Topics Covered;

  • R fundamentals
  • R & supervised learning
  • R & unsupervised learning
  • Final projects & presentations

Prep is the beginner/ foundational stage of the course. Students get introduced to Data Science fundamentals, Python for Data Science, Logic for Data Science, and Data Preparation.

Duration:

8 Weeks

Mode:

Live & Online from 6 pm - 9 pm

Fees:

Ksh 50,000 (USD 500)

At the end of the prep, you will be able to adapt the project life-cycle of a typical data science project while writing code and documenting your workflow in a programming environment.

Course Overview

Topics covered:

  • Fundamentals of Python programming
  • The Data Science Project Life Cycle
  • Ethics in Data Science
  • Tools: Google Colabs/ Jupyter Notebooks

Topics covered:

  • SQL Programming
  • Project Management with Jira

Tools Used:

  • Python
  • Numpy
  • SQL
  • MySQL
  • Git
  • Github
  • Jira.

Topics covered

  • Data Sourcing & Preparation
  • Data Integrity
  • Data Visualization with Python & Tableau

Core is the advanced stage of the course. You will learn how to leverage modern programming languages and tools to analyze real-world data & work on both real-world projects.

Duration:

25 Weeks

Mode:

Hybrid (online & in-person)

Fees:

KSH 150,000(USD 1,500)

At the end of Core, learners will be able to present insights and recommendations from data, work on individual + team projects to build an impressive data scientist portfolio and acquire the confidence needed to succeed in the profession.

Course Overview

Topics Covered

  • Descriptive Analysis
  • Sampling Distribution & Time series
  • Hypothesis testing
  • Final Assessment Week

Topics covered

  • Regression
  • Decision Trees
  • KNN
  • Neural Networks
  • Final Assessment Week

Topics Covered

  • Model Performance
  • Dimensionality Reduction
  • Clustering

Topics Covered;

  • R fundamentals
  • R & supervised learning
  • R & unsupervised learning
  • Final projects & presentations

Data Science is one of the most highly sought-after jobs due to the abundance of data science career pathways and a lucrative pay scale. By the end of the course, graduates will be fit for positions such as:

Data Scientist

Data Scientist

A Data Scientist is a generalist who knows a bit of everything

Being a data scientist entails dealing with all aspects of a project. Often, in big companies, team leaders in charge of people with specialized skills are data scientists; their skill set allows them to overlook a project and guide them from start to finish.

Data Analyst

Data Analyst

Data Analysts prepare reports that effectively show the trends and insights gathered from their analysis.

Data analysts are responsible for different tasks such as visualizing, transforming and manipulating the data. Sometimes they are also responsible for web analytics tracking and A/B testing analysis.

Data Engineer

Data Engineer

Data engineers are responsible for designing, building, and maintaining data pipelines.

They need to test ecosystems for the businesses and prepare them for data scientists to run their algorithms. In short, they make sure that the data is ready to be processed and analyzed.

Data Storyteller

Data Storyteller

Data Storytellers find the narrative that best describes the data to express it to stakeholders

Data Storytelling lies right in the middle of pure, raw data and human communication. A data storyteller needs to take on some data, simplify it, focus it on a specific aspect, analyze its behavior, and use his insights to create a compelling story that helps people better understand the data.

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