
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.
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
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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