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Master Class

If you plan to work as a Data Analyst in Canada, UK, USA, or explore remote jobs from any where in the world, then this training has been specifically designed to set you up for success. 

No tech experience required.


Course overview

Data literacy is critical for decision-making for most industries, and data analytics is a growing field in high demand in the job market. From market research and product development to infrastructure and finance, the need for a foundation in analytics is growing.


Rise to meet the challenges posed by data, and set yourself up for career advancement with our Certificate in Data Analytics

This course prepares you to explore Data Analytics roles, prepares you for job interviews and gives you hands-on experience to drive in the filed of Data and Analytics.  

Here's what you'll benefit from the program;

  • 12 weeks of immersive learning

  • Multiple hands-on Data Analytics projects to add to GitHub

  • Interview preparation  

  • Resume and LinkedIn profile assistance

  • Job placement support

  • Build a Data Analytics Portfolio of projects

  • Recommendation/Reference Letter

  • Alumni networking support


Next class starts on  April 27th, 2024

Course Duration

12 Weeks intensive weekend (Saturday) sessions 

Course Fee (in USD)

$1,300 (One Thousand and Three Hundred Dollars) 

*** Getting an early bird scholarship can reduce your fees by up to 30% (i.e. $900). Closes on March 31st, 2024.

*** Installment payment options exist

Time / Effort

5 - 6 Hours per week for lectures, project work and assessments.

Mode of Course Delivery

100% Online learning


  • This course assumes no prior knowledge or experience of programming. But this knowledge would be an asset.

  • Basic knowledge of statistics and probability expected. (The course only reviews this subject briefly)

  • Access to a computer with an internet connection.

  • Interest in learning new tools or technologies.


The Process 


Candidate completes application form 

Get Interviewed

Candidate is interviewed for program fit

Make Payment

Candidate is admitted and payments made

Start & Complete 

Candidate starts and completes training

Course Modules 

Module 1

Introduction to Data Analytics 

  • The data Life Cycle

  • Planning a Data Analytics Project

  • Tools and Technology Overview

  • Statistics Refresher

Module 2

Python Hello World

  • Python set up

  • Data Types and Data Structures

  • Flow Control

  • Functions, Modules and Libraries

Module 3

Python - Pandas

  • Importing and exporting data

  • Dataframe and Series operations

  • Visualizing data with Pandas

  • Using the Pandas User Guide

Module 4

Databases & SQL

  • Database Fundamental Concepts

  • Structured Query Language (SQL) basics

Module 5

SQL deep dive

  • Join and Aliases

  • Data integration

  • SQL functions

  • Data Aggregation

  • SQL Structured Query Language (SQL) basics

Module 6


  • Excel Basics - Functions, Shortcuts

  • Data Visualization in Excel

  • Group Project Check-in

Module 7

Analysis Techniques and Concepts

  • Pivot Tables (Excel, Pandas)

  • Matching, Grouping, Sorting, Counting

  • Distributions and Outliers

  • Sampling and Probability

Module 8

Data Visualization Deep Dive

  • Types of Visualizations

  • BI Tool Core Concepts (Tableau)

  • Strategies for effective visualizations

Module 9

More on Automation and Sharing Insights

  • Executing SQL using Python

  • Automated Reporting - Examples

  • Case Study - Streamlit

Potential Roles After this Course

Short-term Roles

  • Data Analyst

  • Analytics Consultant

  • Business Intelligence Analyst

  • Quantitative Analyst

  • Operations Analyst

  • Marketing Analyst

  • IT Systems Analyst

  • Logistic Analyst

  • Intelligence Analyst

Long-term Roles

  • Data Scientist

  • Data & Applied Scientist

  • Data Engineer

  • Analytics Engineer

  • Analytics Manager

  • Machine Learning Engineer

Meet the Course Instructors

Yellow Blue Duo Tone Seamless Carousel Instagram Post (Instagram Post (Square)).png

Brian Mukeswe, Canada

Lead  Data Scientist at MasterCard Inc.

Brian leads Data Science efforts for Mastercard Canada., under the company’s Cyber and Intelligence solutions division.  In his role, he leverages data modelling and statistical analysis to inform fraud investigation strategies.

Brian is the lead instructor for Hibreed’s Data Analytics program, and will bring his wealth of experience to support the students as they explore careers in Data Analytics.


Sharon Shamuyarira, Canada

Senior Analyst @ Salesforce

Sharon is a Senior Analyst at Salesforce, under the company’s Global Distribution and Strategy Operation team. In her role she owns key business dashboards, analyzes data on business performance and user adoption.

She holds a Masters in Data Science from the University of Edinburgh. Sharon will be an instructor in Hibreed’s Data Analytics course and will bring her data analysis and coaching skillset to guide the students on their Data Analytics Journey.

Why take this course

Person Analyzing Data

Mock Interview Sessions

Our Talent Acquisition partners will conduct mock interview sessions during the training to give students an opportunity to practice for  real job interviews.
We prepare students according to the current industry trends so that can get interview ready. Students learn how to answer difficult questions, improve communication skills and develop interview strategies.

End to End Live Projects
At Hibreed, our students will get hands-on experience by working on live projects using technical tools in real-time.
Working on real projects will make them more confident and expertise in the respective field.
Students have a group discussions about the projects with other student groups as well as their trainers.

Professional Resume Preparation

Our experts will assist you with job interviews but will also help you to build a perfect resume according to your experience and the work you have done while training.

Our team also help students to optimize their
LinkedIn and Git hub profiles so that they can become prepared and successfully approach the job market.

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