Course Overview
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The Course Benefits



  •  Beginner         (3 Months)
  • Advanced         (3 Months)
  • Full program  (6 Months: Beginner and Advanced)

Course Fee:

  • Registration: 5000 CFA
  • Three-Month Program: 90,000 CFA
  • Six-Month Program: 170,000 CFA

 50% installment is allowed.

About this Course: The Comprehensive Data Science and Analytics Training Program aims to equip participants with foundational and advanced skills in data analysis, machine learning, and data visualization. The program spans six months, with the initial three months focusing on basics and the subsequent three months covering advanced topics.

Phase 1: Basics (3 Months)

Month 1: Introduction to Data Science

  • Overview of data science concepts and methodologies
  • Understanding the data science lifecycle
  • Basics of data collection, cleaning, and preprocessing
  • Introduction to programming languages for data science (e.g., Python, R)

Month 2: Data Analysis and Visualization

  • Exploratory data analysis techniques
  • Data visualization principles and best practices
  • Introduction to data visualization libraries (e.g., Matplotlib, Seaborn)
  • Statistical analysis and hypothesis testing

Month 3: Foundations of Machine Learning

  • Introduction to machine learning concepts and algorithms
  • Supervised learning: regression and classification
  • Unsupervised learning: clustering and dimensionality reduction
  • Model evaluation and performance metrics

Phase 2: Advanced (3 Months)

Month 4: Advanced Machine Learning Techniques

  • Ensemble learning methods (e.g., Random Forest, Gradient Boosting)
  • Deep learning fundamentals and neural networks
  • Natural Language Processing (NLP) techniques
  • Time series analysis and forecasting

Month 5: Big Data Analytics and Tools

  • Introduction to big data concepts and technologies (e.g., Hadoop, Spark)
  • Distributed computing for big data processing
  • Working with big data frameworks and tools (e.g., Apache Spark, Hadoop ecosystem)
  • Implementing machine learning algorithms at scale

Month 6: Applied Data Science Projects

  • Real-world data science projects and case studies
  • Capstone project: applying data science techniques to solve a business problem
  • Presentation and communication of project findings
  • Career development and job readiness workshops

Project Work: Throughout the program, participants will work on hands-on projects and case studies to apply their knowledge and skills in practical scenarios.


  • Regular quizzes, assignments, and coding exercises to assess understanding
  • Evaluation of project deliverables and presentations
  • Final project demonstrating proficiency in data science and analytics

Certification: Upon successful completion of the program and passing the final assessment, participants will receive a certificate of completion in Comprehensive Data Science and Analytics.

10 Benefits of the Training

  1. Enhanced Employability: Participants gain highly sought-after skills in data science and analytics, opening doors to a wide range of job opportunities in various industries.
  2. Lucrative Career Opportunities: Proficiency in data science and analytics positions individuals for high-paying roles such as data scientist, data analyst, and machine learning engineer.
  3. Data-Driven Decision Making: Trained professionals can leverage data analysis techniques to extract valuable insights and inform strategic decision-making processes within organizations.
  4. Improved Business Performance: Data-driven insights enable organizations to optimize processes, identify growth opportunities, and enhance overall business performance.
  5. Predictive Analytics: Understanding machine learning algorithms empowers individuals to build predictive models that forecast future trends and outcomes, helping organizations stay ahead of the competition.
  6. Enhanced Problem-Solving Skills: Data science training cultivates analytical thinking and problem-solving abilities, valuable skills applicable across various domains.
  7. Data Visualization Proficiency: Trained professionals can effectively communicate insights and findings through compelling data visualizations, facilitating better understanding and decision making.
  8. Innovation and Creativity: Data science training fosters innovation by enabling individuals to discover new patterns, trends, and opportunities hidden within data.
  9. Personal Development: Mastery in data science and analytics brings a sense of accomplishment and personal growth as individuals tackle complex challenges and drive positive change through data-driven insights.
  10. Contribution to Societal Impact: Data science skills can be applied to address pressing societal challenges in areas such as healthcare, education, and environmental sustainability, making a meaningful impact on society.