Data Analysis (for regulars)

Chuka Uzo

This curriculum provides a strong foundation in both the technical aspects of data analytics and the practical skills needed to build full-stack applications. Students will gain hands-on experience with a wide range of tools and technologies, preparing them for real-world data analytics challenges.

250,000.00 / month for 2 months and a 50,000.00 sign-up fee



Data Analytics Cohort (Regular)

Duration: 8 Weeks


– Weeks 1-2: Python and Pandas for Data Manipulation
– Goals: Master data manipulation and analysis using Python and Pandas. Understand data structures, data cleaning, and preliminary data analysis techniques.
– Milestone: Complete a series of exercises to manipulate and prepare datasets for analysis.


Weeks 3-4: SQL for Data Storage and Retrieval
– Goals: Learn to use SQL for managing databases, executing queries, and retrieving data. Explore relational database concepts and practice writing complex SQL queries.
– Milestone: Design and query a database using SQL to solve a specific data retrieval problem.


Weeks 5-6: Building Full-Stack APIs
– Goals: Dive into backend development with Flask API for Python to create RESTful APIs. Introduction to Node.js for building scalable network applications.
– Milestone: Develop a simple RESTful API with Flask that interacts with a SQL database, and a basic application using Node.js that can consume this API.


Weeks 7: Data Visualization with Grafana or Tableau
– Goals: Learn the fundamentals of data visualization and how to use Grafana or Tableau for creating interactive dashboards and reports.
– Milestone: Create a dashboard that visualizes data processed by your Flask API, showcasing key insights.


Week 8: Capstone Project and Review
– Goals: Apply all learned skills to develop a full-stack data analytics project. This includes data collection and processing with Python and Pandas, data storage and retrieval with SQL, an API built with Flask, and visualization with Grafana or Tableau.
– Milestone: Present a comprehensive project that demonstrates the ability to build and deploy a full-stack data analytics application.




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