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Artificial Intelligence Course in Toronto, Canada

4.9 ( 334 ) Ratings

Our Artificial Intelligence course in Toronto is an industry-designed course for learning TensorFlow, artificial neural networks, perceptron in neural networks, transfer learning in Machine Learning, backpropagation for training networks, etc. through hands-on projects and case studies. Get the best online Artificial Intelligence training in Toronto from Artificial Intelligence certified experts. It is created in collaboration with IBM.

Key Highlights

44 Hrs Instructor Led Training
24 Hrs Self-paced Videos
48 Hrs Project & Exercises
Certification and Job Assistance
Flexible Schedule
Lifetime Free Upgrade
24 x 7 Lifetime Support & Access
Mentor Support
Intellipaat-Key-Features
Intellipaat-Key-Features
Intellipaat-Key-Features

Artificial Intelligence Course in TorontoOverview

We provide one of the best AI courses in Toronto, Canada, which offers definitive training for mastering the details of AI and Machine Learning. Through this training, you will get hands-on experience in designing artificial neural networks, the techniques of supervised and unsupervised learning, logistic and linear regression, vectorization, binary classification, coding using the Python language for Machine Lear...

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What you will learn in this best Artificial Intelligence course in Toronto?

Through this Artificial Intelligence course in Toronto, you will able to master the below-mentioned skills:

  • Introduction to Artificial Intelligence
  • Various components of AI and its subsets
  • Application of convolutional neural networks
  • Numerical computing using TensorFlow
  • Tensor Processing Unit
  • Various Machine Learning methodologies
  • Applications of AI in real-world scenarios
  • Professionals in analytics, Data Science, e-commerce, and search engine domains
  • Software professionals looking for a career switch
  • Fresh graduates

Anybody can take up this Artificial Intelligence course in Toronto with placement regardless of their prior skills.

Toronto is the financial and commercial capital of Canada. It has some of the biggest and best enterprises that are deploying Artificial Intelligence technologies at scale. If you are trained in Artificial Intelligence along with Deep Learning then you can benefit from the huge number of job opportunities in Artificial Intelligence available in Toronto, Canada.

Toronto is a top technology hub of Canada and futuristic technologies like Artificial Intelligence are extensively deployed in this city making it the hotbed for some really good AI start-ups and also well-entrenched players. Getting the right training in AI can help you make the best use of this boom in AI market in Toronto.

Today, Artificial Intelligence has conquered almost every industry. Within a year or two, nearly 80 percent of emerging technologies will be based on AI. Machine Learning, especially Deep Learning, the most important aspect of Artificial Intelligence, is used by AI-powered recommender systems (chatbots) and search engines for online customer recommendations. Therefore, to remain relevant and gain expertise in this emerging technology, enroll in Intellipaat’s AI course in Toronto.

Here are a few reasons why Artificial Intelligence is a great career option:

  • There are over 35,000 job opportunities available for AI professionals in the United States alone – LinkedIn
  • AI Engineers earn over US$114k per annum in the United States – Glassdoor

This will help you build a solid AI career by grabbing the best Artificial Intelligence Engineer positions in leading organizations.

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Artificial Intelligence would be the ultimate version of Google - Larry Page
The global Artificial Intelligence market size is expected to grow at a compound annual growth rate (CAGR) of 42.2% from 2020 to 2027 - Grand View Research

Career Transition

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Skills Covered

  • Deep Learning
  • Neural Networks
  • TensorFlow
  • Keras
  • Deep Neural Networks
  • Convolutional Neural Networks
  • Kernel
  • GPU
  • Restricted Boltzmann Machine (RBM)
  • Natural Language Processing (NLP)
  • Chatbots
  • Time-series Predictions
  • Long Short-term Memory (LSTM)
  • Autoencoders
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Course Fees

Self Paced Training

  • 24 Hrs e-learning videos
  • Lifetime Free Upgrade
  • 24 x 7 Lifetime Support & Access

$281

Online Classroom Preferred

  • Everything in self-paced, plus
  • 44 Hrs of Instructor-led Training
  • 1:1 Doubt Resolution Sessions
  • Attend as many batches for Lifetime
  • Flexible Schedule
08 Aug

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

14 Aug

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

21 Aug

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$ 449 $349 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Artificial Intelligence Course Content in Toronto

Live Course

Module 01 - Introduction to Deep Learning and Neural Networks

Preview

1.1 Field of machine learning, its impact on the field of artificial intelligence
1.2 The benefits of machine learning w.r.t. Traditional methodologies
1.3 Deep learning introduction and how it is different from all other machine learning methods
1.4 Classification and regression in supervised learning
1.5 Clustering and association in unsupervised learning, algorithms that are used in these categories
1.6 Introduction to ai and neural networks
1.7 Machine learning concepts
1.8 Supervised learning with neural networks
1.9 Fundamentals of statistics, hypothesis testing, probability distributions

Module 02 - Multi-layered Neural Networks

Preview

2.1 Multi-layer network introduction, regularization, deep neural networks
2.2 Multi-layer perceptron
2.3 Overfitting and capacity
2.4 Neural network hyperparameters, logic gates
2.5 Different activation functions used in neural networks, including relu, softmax, sigmoid and hyperbolic functions
2.6 Back propagation, forward propagation, convergence, hyperparameters, and overfitting.

3.1 Various methods that are used to train artificial neural networks
3.2 Perceptron learning rule, gradient descent rule, tuning the learning rate, regularization techniques, optimization techniques
3.3 Stochastic process, vanishing gradients, transfer learning, regression techniques

4.1 Understanding how deep learning works
4.2 Activation functions, illustrating perceptron, perceptron training
4.3 multi-layer perceptron, key parameters of perceptron;
4.4 Tensorflow introduction and its open-source software library that is used to design, create and train
4.5 Deep learning models followed by google’s tensor processing unit (tpu) programmable ai
4.6 Python libraries in tensorflow, code basics, variables, constants, placeholders
4.7 Graph visualization, use-case implementation, keras, and more.

5.1 Keras high-level neural network for working on top of tensorflow
5.2 Defining complex multi-output models
5.3 Composing models using keras
5.3 Sequential and functional composition, batch normalization
5.4 Deploying keras with tensorboard, and neural network training process customization.

6.1 Using tflearn api to implement neural networks
6.2 Defining and composing models, and deploying tensorboard

7.1 Mapping the human mind with deep neural networks (dnns)
7.2 Several building blocks of artificial neural networks (anns)
7.3 The architecture of dnn and its building blocks
7.4 Reinforcement learning in dnn concepts, various parameters, layers, and optimization algorithms in dnn, and activation functions.

8.1 What is a convolutional neural network?
8.2 Understanding the architecture and use-cases of cnn
8.3‘What is a pooling layer?’ how to visualize using cnn
8.4 How to fine-tune a convolutional neural network
8.5 What is transfer learning?
8.6 Understanding recurrent neural networks, kernel filter, feature maps, and pooling, and deploying convolutional neural networks in tensorflow.

9.1 Introduction to the rnn model
9.2 Use cases of rnn, modeling sequences
9.3 Rnns with back propagation
9.4 Long short-term memory (lstm)
9.5 Recursive neural tensor network theory, the basic rnn cell, unfolded rnn,  dynamic rnn
9.6 Time-series predictions.

10.1 Gpu’s introduction, ‘how are they different from cpus?,’ the significance of gpus
10.2 Deep learning networks, forward pass and backward pass training techniques
10.3 Gpu constituent with simpler core and concurrent hardware.

11.1 Introduction  rbm and autoencoders
11.2 Deploying rbm for deep neural networks, using rbm for collaborative filtering
11.3 Autoencoders features and applications of autoencoders.

12.1 Image processing
12.2 Natural language processing (nlp) – Speech recognition, and video analytics.

13.1 Automated conversation bots leveraging any of the following descriptive techniques:  Ibm watson, Microsoft’s luis, Open–closed domain bots,
13.2 Generative model, and the sequence to sequence model (lstm).

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Artificial Intelligence Assignments and Projects

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends – the possibilities are endless and our community has something for everyone!

Artificial Intelligence Certification in Toronto

The entire content of this AI course is developed by leading AI professionals to help you find the best a\Artificial Intelligence Engineering jobs at top MNCs. During the certification training, you will work on real-world projects that will help evaluate your skills and learning in real-time business scenarios, thus helping you accelerate your career effortlessly.

Upon the completion of this online Artificial Intelligence course in Toronto, there will be quizzes that reflect the type of questions asked in the certification exam and will help you score better.

Intellipaat’s course completion certificate will be awarded on the completion of the project work (after expert review) and scoring at least 60 percent marks in the quiz. This certification is well-recognized by top 80+ MNCs such as Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.

Artificial Intelligence Training Reviews in Toronto

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FAQs on the Artificial Intelligence Course

What is Intellipaat’s best Artificial Intelligence course in Toronto, Canada?

Our Artificial Intelligence online training involves the participation of both learners and instructors in an online environment. Being a learner, you can log in to our applied AI course sessions from anywhere and attend the class without having to be present physically. Also, we record the proceedings of all our AI classes to further enhance your learning process. On the completion of this online AI training in Toronto, your experience will be equivalent to that of a professional who has worked for 6 months in the industry.

Intellipaat is the leading provider of Artificial Intelligence courses in Toronto. The courses such as Machine LearningData ScienceData Analytics, R programming language, and others help you become job-ready by focusing on the practical implementations of the concepts in real-time live projects.

At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering the 24/7 query resolution, and you can raise a ticket with the dedicated support team at anytime. You can avail of the email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our trainers.

You would be glad to know that you can contact Intellipaat support even after the completion of the training. We also do not put a limit on the number of tickets you can raise for query resolution and doubt clearance.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.

Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.

Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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