Data Science Fundamentals Training.


This live, guided training, offered both online and in-person, is tailored for individuals aspiring to embark on a career path in Data Science.

Upon completion of this program, participants will have the proficiency to:

  • Set up and fine-tune Python and MySQL environments.
  • Comprehend the scope of Data Science and its capacity to enhance business operations across industries.
  • Acquire essential Python programming skills.
  • Master both supervised and unsupervised learning algorithms in Machine Learning and apply them to interpret data findings.

Course Dynamics:

  • Interactive sessions combined with thoughtful discourse.
  • Extensive hands-on practice.
  • Direct application of concepts in a controlled lab setting.

Personalization of the Course:

  • For a training experience adapted to your specific requirements, please get in touch to discuss customization options.


Course Outlines

Day 1 

  • Data Science: an overview
  • Practical part: Let’s get started with Python – Basic features of the language 
  • The data science life cycle – part 1
  • Practical part: Working with structured data – the Pandas library

Day 2 

  • The data science life cycle – part 2
  • Practical part: dealing with real data
  • Data visualisation
  • Practical part: the Matplotlib library

Day 3

  • SQL – part 1
  • Practical part: Creating a MySql database with tables, inserting data and performing simple queries 
  • SQL part 2
  • Practical part: Integrating MySql and Python 

Day 4

  • Supervised learning part 1
  • Practical part: regression
  • Supervised learning part 2
  • Practical part: classification

Day 5

  • Supervised learning part 3
  • Practical part: building a spam filter
  • Unsupervised learning
  • Practical part: Clustering images with k-means


  • An understanding of mathematics and statistics.
  • Some programming experience, preferably in Python.


  • Professionals interested in making a career change 
  • People curious about Data Science and Data Analytics