The machine learning and artificial intelligence course typically covers the principles, algorithms, and techniques used in creating intelligent systems that can learn and make predictions or decisions based on data. The course would cover topics such as supervised and unsupervised learning, regression and classification models, deep learning, neural networks, reinforcement learning, and natural language processing.
Professional Diploma in Machine Learning and
Artificial Intelligence is a premium programme offered by Pedagog, approved and
awarded by European International
University-Paris.
Course content:
Students are required to complete Performance-based assessment task involving machine learning model development and evaluation and may gain experience in designing and implementing intelligent systems.
On successful completion of the course, the
student will be awarded an Internationally accredited
Diploma Certificate from EIU-PARIS,
evidencing your competitive advantage locally and Internationally.
THE DUAL CERTIFICATE is awarded by
EIU-Paris (University) and Pedagog.
Please Note: A Hard Copy of certificate from the
university can be requested at an additional minimal fee, via e-mail
to hello@pedagog.ac
The course would be geared towards students with a strong background in programming, mathematics, and statistics, and may prepare students for careers in data science, artificial intelligence, or software engineering.
Upon completion of the programme, graduates can pursue careers as data analysts, data scientists, database administrators, business intelligence analysts, and software developers in a wide range of industries, including finance, healthcare, technology, and government.
BF
Babajide Fakile
05:00:00 PM 2024-01-04
The course is very complete and the explanations are very good for cumbersome topics in particular for the probability and statistics section. However, it is so complete that for someone who went through a good business bachelor, or a STEM course, at least half of the course will be with little value added. For someone who has very weak mathematical and statistical background this course is fantastic, and I would absolutely recommend it. I think those topics should be on the appendix and instead bring the panda's section to an earlier and not appendix part of the course. The last case is the best, and even if someone with background could discuss some decisions, the explanation of the steps and the layout of the code is very step by step and beginner friendly. Overall the course is great for absolute beginners but not so much for people with quantitative background
European International University - Paris
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