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Your Learner Verification

This is to verify that Mustafa Jarwan has completed the course Data Science Fundamentals - Essential Tools & Concepts on Alison.

Mustafa Jarwan

Alison ID: 59326992

Course Completed: Data Science Fundamentals - Essential Tools & Concepts

Date of Completion: 19th October 2026

Email: [email protected]

Total Study Time: 6h 13m

Final Assessment Score:

Alison courses requires at least
70% to pass the final assessment

96%
CPD Hours Completed:

CPD approved learning hours
completed through this course

5-7h

Course Information

Learn about the relationship between data science and A.I. machine learning technology in this free online course.

Data science and machine learning (ML) represent two wonders of modern technological advancement and make a profound impact on the world around us. Digital Partner has developed this course to help you understand these fields' basic framework and functionality. The course is divided into two modules: the first covers data sciences and the second focuses on the basics of machine learning.

We first introduce you to data science and lay out its advantages and essential components. We also discuss the many applications of data science. We then trace the relationship between machine learning and data sciences and explain various workflows that make up data science, including the ‘Obtain, Scrub, Explore, Model and iNterpret’ (OSEMN) workflow, Blitzstein and Pfister's workflow and the CRISP-DM workflow.

The course's second module shifts towards ML and related fields. We explain the basics of machine learning and go over common ML outflows. We also discuss different clustering methods, regression and their types. Finally, the course discusses deep learning, neural networks and the relationship between them. Sign up for this course to start building a solid foundation in data science and machine learning and learn how artificial intelligence can be harnessed to drive today’s research.

Modules Completed

Module 1: Understanding the Data Science Field
Module 2: Machine Learning Basics
Module 3: Course assessment

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