Data Science and Data Analytics Training

Name: Formation Data Science et Data Analytics
Brand: ODIB SERVICES
SKU: 6a71ab07361d79.73252104

Catégorie : Courses & Training • Marque : ODIB SERVICES

#formation #data #science #analytic #cours formation #odib services

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Zone d'intervention : Womey yenawa Abomey-Calavi

Delivery zones: Cotonou Lomé

Training in Data Science and Data Analytics should cover the basics of statistics, Python, SQL and database management. It must then train learners in analysis, in the visualisation of data (Excel, Power

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Detailed description

For comprehensive training in Data Science and Data Analytics, modules can be organized in a progressive manner, from beginner to advanced.

Block 1: Fundamentals

1. Introduction to Data Science and Data Analytics

2. Mathematics for data science

Descriptive statistics

Probabilities

Linear algebra

3. Introduction to databases

Block 2: Programming

4. Python for data analysis

5. R for statistics (optional but useful)

6. SQL for database query

7. Git and GitHub (version management)

Block 3: Data Analysis

8. Data cleaning and preparation

9. Exploratory Data Analysis (EDA)

10. Data visualization with Excel, Power BI, Tableau and Python (Matplotlib, Plotly)

Block 4: Applied statistics

11. Inferential statistics

12. Linear regression and logistics

13. Time series

14. Hypothesis tests

Block 5: Machine Learning

15. Introduction to Machine Learning

16. Supervised learning

17. Unsupervised learning

18. Model evaluation and optimization

Block 6: Big Data and Cloud

19. Introduction to Big Data

20. Apache Spark

21. Hadoop (notations)

22. Introduction to the Cloud (AWS, Azure or Google Cloud)

Block 7: Artificial Intelligence

23. Deep Learning

24. Automatic natural language processing (NLP)

25. Computer Vision

26. IA general (LLM, ChatGPT, etc.)

Block 8: Business Applications

27. Data Analytics for Finance

28. Data Analytics for Health

29. Data Analytics for Agriculture

30. Business Intelligence (BI)

Block 9: Reporting results

31. Creating interactive dashboards

32. Storytelling with data

33. Preparation of analytical reports

Block 10: Professional project

34. Project to complete training on actual data

35. Construction of portfolio

36. Preparation for certifications and job interviews

Software and tools to master

Excel (advanced)

SQL

Python

Power BI

Table

Jupyter Notebook

Google Colab

GitHub

VS Code

For 6 months of vocational training, these modules can be divided into three levels:

Level 1 (beginner): Excel, Statistics, SQL, Basic Python.

Level 2 (Intermediary): data analysis, Power BI, Table, regression, time series.

Level 3 (Advanced): Machine Learning, Deep Learning, Big Data, Cloud, Professional Project.

This progress allows participants to acquire skills that are directly exploitable in the company while building a solid foundation for advancing to Advanced Data Science.