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À propos

Faculté

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Machine Learning

Master industry-standard tools and techniques such as Search Engine Optimization (SEO), Social Media Marketing, Google Ads, Conversion Optimization, Google Analytics, digital content marketing, marketing automation, and front-end web development.

Skills gained : Modular thinking, Programming basics,
Algorithimic thinking, Problem solving, Debugging

Attend an Info Session

36 hours
Schedule : Mon - Wed - Thu
6 PM - 9 PM

Duration

Modular thinking,
Programming basics,
Algorithimic thinking,
Problem solving
Debugging

Skills Gained

Java, ASP,
Microsoft .Net, SQL server
Object Oriented
Programming, ORM,

Tools

Course Fee ; 2500
Bundle price available
Request Corporate
vouchers

Pricing

Aperçu du programme

The Machine Learning Course is a comprehensive and practical introduction to the field of machine learning. Designed for both beginners and those with some prior experience, this course covers the key concepts, algorithms, and techniques used in machine learning. Through a combination of theoretical learning, hands-on coding exercises, and real-world projects, participants will gain a deep understanding of machine learning and its applications.

Start Date

Duration

30 Hours

Tuition Fee

Contact the Advisor

13 juin 2025

Avantages clés

Get trained by industry Experts

Our courses are delivered by professionals with years of experience having learned first-hand the best, in-demand techniques, concepts, and latest tools.

Official Certification curriculum

Our curriculum is kept up to date with the latest official Certification syllabus and making you getting ready to take the exam.

Tax Credit

Claim up to 25% of tuition fees and education tax credit from your taxes.

Discount on Certification Voucher

Upto 50 percent discount voucher will be provided.

24/7 Lab access

Our students have access to their labs and course materials at any hour of the day to maximize their learning potential and guarantee success.

Course Outline

Introduction to Machine Learning

Data Preprocessing and Exploration

Supervised Learning Algorithms

Unsupervised Learning Algorithms

Model Evaluation and Validation

Neural Networks and Deep Learning

Computer Vision

Model Deployment and Ethics

Advanced Topics and Future Trends

Skills gained

Key concepts and principles of machine learning.

Proficiency in programming languages.

Ability to preprocess, clean and transform data for machine.

Understanding of various machine learning algorithms.

Proficiency in applying supervised and unsupervised learning

Experience in using popular machine learning frameworks.

Knowledge of deep learning and neural networks.

Natural language processing (NLP) techniques.

Knowledge of time series analysis.

Experience in evaluating and selecting appropriate machine.

Qui peut postuler

L'éducation pratique en TI est le pont entre votre diplôme et votre carrière.

Eligibility Criteria

Learners need to possess an undergraduate degree or a high school diploma. 

Prerequisites

Knowledge on Statistics and Python programming are required to enroll in the course.

Upcoming sessions & Schedule

Enroll

Summer Session

12 févr. 2025

Register before

11 févr. 2025

Fall Session

13 juin 2025

Register before

12 juin 2025

Remind

Winter Session

8 oct. 2025

Register before

7 oct. 2025

Contactez-nous

Enroll for this
Certification

20th June
Start Date


Stand alone Certification

Enroll

Get Bundle
pricing

Get Bundle

Three Certifications
Bundle

Attractive
Bundle price for three

Contactez-nous

FAQs

About the Instructor?

Is there any Voucher to take the Official certification?

I need help in choosing the correct courses for my job role. Can you assist?

When do I get the MCIT Certificate?

Collège de technologie de l'information de Montréal

Collège des technologies de l’information de Montréal

200-1255 Robert-Bourassa Blvd.

Montreal, Quebec H3B 3B2

+1 514 405 6874

[email protected]