Data Science & Machine Learning – September Cohort

This cohort is structured to provide an in-depth understanding of both the theoretical foundations and practical applications of data science and machine learning.

Cohort Overview

The May cohort for the Data Science & Machine Learning program is a comprehensive learning pathway designed to equip participants with the skills and knowledge required to excel in the fields of data analytics, predictive modeling, and artificial intelligence.

 

This cohort is structured to provide an in-depth understanding of both the theoretical foundations and practical applications of data science and machine learning.

 

This cohort is ideal for aspiring data scientists, analysts, and anyone looking to transition into the field of artificial intelligence and machine learning with a solid, practical foundation.

What's Included

  • Fundamental concepts of statistics, probability, and data analysis.
  • Data cleaning, preprocessing, and exploratory data analysis techniques.
  • Machine learning algorithms, including supervised and unsupervised learning.
  • Deep learning introduction and neural network applications.
  • Real-world projects and case studies to bridge theory with practice.
  • Access to mentorship from industry professionals.
  • Interactive lectures and hands-on workshops.
  • Collaborative learning with peers to foster teamwork skills.

Key Details

Training begins on September 1, 2026. Applications close on August 26, 2026. Early enrollment is encouraged as seats fill quickly.

Twelve weeks of structured learning from September 1, 2026 through December 1, 2026. Total commitment is approximately twenty hours per week including live sessions and independent work.

Classes meet Tuesdays, Thursdays, and Saturdays from 10:00 AM to 1:00 PM West Africa Time. Sessions are live and interactive with recorded access for asynchronous review.

This cohort is delivered live online via Zoom. You will need a stable internet connection, a laptop or desktop computer, and design software access. Technical support is available throughout the program.

This cohort is led by Chioma Adeyemi and Zainab Hassan, both with extensive experience in digital product design and user experience across African and global markets.

Only limited (25) seats is available for this cohort. Enrolment is limited to 25 students to ensure personalized instruction and meaningful peer interaction throughout the program.

Full payment is ₦260,000. Instalment plans are currently not available. Secure online payment and bank transfer are both accepted.

Upon completion with eighty-five percent attendance, you receive a professional certificate from NovelTech Academy. This credential is recognized by employers and can be shared on LinkedIn and professional profiles.

Instructors

Your Instructors

This cohort is led by approved instructors with experience in the subject area.

Daniel Johnson

Data Scientist

Daniel Johnson specialises in applying machine learning and predictive analytics to solve real-world problems.

  • Attendance

    Completion Requirements

    To successfully complete this cohort and receive a certificate, learners must attend scheduled sessions and meet participation requirements. A minimum attendance threshold applies.

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    Process

    Registration and Enrolment Process

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    Confirmation

    Approved applicants receive instructions for tuition payment and cohort access.

    Learning

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