ALX Data Science Program Overview

Jun 25, 2025

Overview

This lecture introduces the ALX Data Science Program, outlining its structure, key learning areas, and the skills and careers it prepares students for.

Program Structure

  • The program begins with a 3-month Professional Foundations module covering communication, leadership, and career skills.
  • Core data science modules are divided into weekly sprints with assignments to track progress and reinforce learning.
  • Students should expect to dedicate 35-40 hours per week to coursework and peer collaboration.
  • Training content is released weekly to ensure steady progress.

Core Learning Areas

  • Students learn to use spreadsheets and master statistics and data modeling.
  • The program covers database management skills using SQL.
  • Data visualization is taught using Power BI.
  • Python programming is a key component of the curriculum.
  • The final module focuses on cloud computing applications in data science.

Skill Development & Career Pathways

  • Students engage in practical projects to apply their data science skills in real-world scenarios.
  • The program prepares graduates for roles such as Data Scientist, Advanced Analyst, Machine Learning Engineer, or Cloud Computing Practitioner.
  • Graduates receive a certificate of completion that is recognized in the tech industry.

Key Terms & Definitions

  • Data Science — the practice of analyzing and interpreting complex data to aid decision-making.
  • Cloud Computing — delivering computing services like storage and processing over the internet.
  • Machine Learning — a type of AI that enables systems to learn from data and improve over time.
  • Data Modeling — designing the structure of a database and relationships within data.
  • Power BI — a Microsoft tool for visualizing and analyzing data.
  • SQL — a programming language for managing databases.

Action Items / Next Steps

  • Commit to the required weekly learning hours and complete assigned modules.
  • Engage actively with peers on collaborative projects.
  • Complete all assignments and practical projects.
  • Upon completion, obtain your certificate and explore career opportunities in data science.