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Data Science continues to evolve as one of the most promising, in-demand career paths for skilled professionals in Kenya. Our curriculum has been curated by domain experts through research and use of real-world case studies and data-sets relevant to the Kenyan context

Application Deadline: 20th September 2019 (Prep class)

Start Date: 14th October 2019 (Prep class)

Graduation: 15th November 2019 (Prep class)

Application Form


 

Data science is a multidisciplinary field using software and algorithms to uncover insightful findings from data to enable companies to make smarter business decisions. It employs concepts, techniques and theories drawn from the fields of mathematics, statistics, information science and computer science.

 
Why Learn Data Science?

In recent years, digital information has become so essential that organisations use different kinds of data every day. Unfortunately, not many professionals have the capability to process and provide insights from this data. This is evident in the Kenyan and African context where many organisations lack data teams skilled enough to provide meaningful insights and analysis to drive growth and innovation.

Here at Moringa School, you can grow to become a Junior Data Scientist with the skills to act as a consultant to organisations by understanding the complex behaviors, trends and characteristics within the collected and accumulated data. Moringa School have partnered with Dalberg Data Insights who will be providing the real-world data sets for this program.


Dalberg Data Insights is part of a global group named Dalberg in the data science field. They design solutions to international development challenges using data. Their specialization areas include:

  1. Food Security
  2. Gender Data Gap
  3. Financial Inclusion
  4. Disease Surveilance
  5. Data-as-a-Service (DAAS)
  6. Mobility and Urban Planning

After graduating from Moringa, you will have a highly technical skill set in data science that is very desirable in the Kenyan job market today.

In the Moringa Data Science course, you will learn the essential data science skills needed to solve complex business problems. In addition, you will learn essential non-technical skills that will help you communicate your findings to stakeholders in the workplace, who will make decisions based on your findings.

Every day, as a data science student, you will take on real-world business problems and case studies and analyze data sets for new insights. Ultimately, you present your findings using statistics, critical thinking and business knowledge.

 
Full Duration (Prep & Core)

The prep program is a prerequisite class before the core program. This class is five weeks long and the core program lasts 18 weeks.

 
Overall Course Goals (Prep & Core)

By working on projects individually or in teams, you will apply your new data analytical skills towards building an impressive data analysis portfolio, as well as build the self-confidence needed to succeed in today’s data-driven economy.

 
Overall Learning Objectives (Prep & Core)

By the end of the course, you will be able to:

  1. Source and store data
  2. Perform data visualisation
  3. Present insights and recommendations from data to solve complex business problems
Data Science Prep:

KSh 40,500 (for a 5-week immersive program)

Data Science Core:

KSh 160,000 (for an 18-week immersive program)

 

NOTE: Students who go through the prep program automatically get a discount of KSh 20,000 on the core program thus only paying KSh 140,000.

 

Learning Outcomes for Data Science Prep (5 Weeks)
Each data science topic in the Moringa Data Science Prep curriculum culminates with a summative assessment which aims to test your knowledge and understanding of that topic. It is also a way of evaluating your understanding and achievement of the following learning outcomes:

  1. Introduction to Data Science
    By the end of this unit, you should be able to:
    1. Understand what it takes to become a data scientist
      Subtopic: Becoming a data scientist
    2. Adapt the project life-cycle of a typical data science project
      Subtopic: the data science project lifecycle
    3. Demonstrate a sophisticated awareness of ethical implications relevant to the use of data
      Subtopic: Ethics in data science

    Tools: Standups, Check-ins, CRISP-DM.

  2. Logic for Data Science
    By the end of this unit, you should be able to:
    1. Write code and document your workflow in a programming environment
      Subtopic: Workflow and version control
    2. Recall the basics of Python programming for data science
      Subtopic: Subtopic: Python programming
    3. Obtain and manipulate data from various types of databases using the SQL language
      Subtopic: SQL programming
    4. Manage a team deliverable using a standard project management tool
      Subtopic: Project management with Jira

    Tools: Python, Numpy, SQL, MySQL, Postgres, Git, Github, Jira.

  3. Data Preparation
    By the end of this unit, you should be able to:
    1. Evaluate the integrity of data by making decisions on data quality issues
    2. Perform the extraction, querying and aggregation of data for analysis in multiple projects through common techniques and tools
    3. Understand mechanisms for missing data, outliers and analytic implications

    Tools: Python, Pandas, Matplotlib.

Course Topics for Data Science Core (15 Weeks)
Because of the proprietary nature of our Data Science Full-time Course. The Course Outline for Data Science Core Program is only available to those students who go through our Data Science Prep Program or to you, if you visit our Nairobi Campus for a brochure.

Overall Learning Objectives for Data Science Core (15 Weeks)
By the end of the course, you will have become a Junior Data Scientist. This means you will be able to:

  1. Analyze and Visualize Data
  2. Model Data
  3. Present insights and recommendations from data to solve complex business problems

Through working on projects individually or in teams, you will apply your new data science analytical and modeling skills towards building an impressive data scientist's portfolio and the confidence needed to succeed in today’s data-driven economy.





Kamande currently leads Data Science at mSurvey, a platform that powers Integrated Customer Experience in Africa. In this role, he provides data support for current products and develops new Data products to drive consumer understanding through advanced analytics and machine learning. He holds a Masters’ degree in Statistics and a Masters’ degree in Computational Intelligence from The University of Nairobi and previously worked at Nielsen as a Data Science Associate for East Africa. See full Profile on LinkedIn

Samuel Kamande Wambui