
AI & Machine Learning
Michael Shimels
ML, DL & AI Instructor
Guides machine learning, deep learning and applied AI project tracks.
Course detail
Neural network foundations, modern model concepts and applied deep learning workflows.

13th round and summer intake
Online classes are live and recorded. In-person learners can choose regular, extension or weekend attendance when available.
Understand deep learning
Train neural models
Prepare for computer vision and NLP

Course experience
Each monthly part should combine instructor-led lessons, resources, checklists, practice work and evaluation gates before learners move on.


Outline highlights
Learn from practitioners who ship production software, campaigns and creative work — then guide your evaluations in the LMS.

AI & Machine Learning
ML, DL & AI Instructor
Guides machine learning, deep learning and applied AI project tracks.
Resources are organized by term, monthly part, week and lesson. Full Stack access opens one part at a time after payment and instructor evaluation.
Unlock after payment or instructor evaluation.
Unlock after payment or instructor evaluation.
Best for students who want structured lab access, instructor support and consistent weekday practice.
Designed for learners who need evening sessions three days per week after work or daytime study.
A practical option for working learners and university students who need weekend attendance.
Live virtual classes are recorded so students can review lessons, recap missed points and continue studying after class.
Available for courses longer than three months when tuition is paid in full.
Available when one student registers for two or three courses.
Special support for students who did not pass university entrance and are not eligible for remedial placement.
For online Full Stack enrollment, one eligible family member can receive tuition waived under the family offer.
Machine Learning3 months
AI concepts, responsible use, model workflows and practical applications for modern careers.
Machine Learning3 months
Machine learning foundations with data preparation, model training, evaluation and applied projects.
Technology3 months
Image processing and vision model workflows for inspection, recognition and intelligent applications.
Technology3 months
Text processing, language models and practical NLP applications for search, assistants and analysis.