Deep Learning with Keras Training in Ontario

Deep Learning with Keras Training in Ontario, Canada

Master Keras to build and train neural networks with a user-friendly, high-level API.

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Deep Learning with Keras Training is a professional training program delivered by ProgNXT in Ontario, Canada. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this Deep Learning with Keras Training course with hands-on, instructor-led sessions. The Deep Learning with Keras training offers a practical introduction to designing, building, and deploying deep learning models using the Keras...

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: PRQ32
14 Hrs
Last Updated: April 2026

Course Rating5/5

The Deep Learning with Keras training offers a practical introduction to designing, building, and deploying deep learning models using the Keras library. Participants will explore key concepts such as neural network architecture, activation functions, loss functions, and model optimization while leveraging Keras's user-friendly API. Through hands-on exercises, this training enables participants to implement and fine-tune deep learning models for applications like image classification, text processing, and predictive analytics.

Welcome to the official Deep Learning with Keras Training certification program in Ontario, Canada. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic understanding of Python programming
Familiarity with linear algebra and calculus fundamentals
Awareness of machine learning concepts (helpful but not mandatory)
Experience with TensorFlow (helpful but not mandatory)

Upon completing the Deep Learning with Keras course, participants will:

Gain hands-on experience with Keras for building and training deep learning models.
Understand the architecture and working of deep learning models such as feed-forward neural networks, CNNs, and RNNs.
Learn how to implement and optimize deep learning models for image, text, and time-series data.
Be able to use pre-trained models for transfer learning and fine-tuning.

Deep Learning Model Construction: Ability to build, train, and optimize neural networks using Keras.
Model Evaluation and Optimization: Understanding how to evaluate model performance and improve it using various techniques.
Convolutional Neural Networks (CNNs): Proficiency in implementing CNNs for image classification tasks.
Recurrent Neural Networks (RNNs): Skills to work with RNNs for sequence data processing.

Transfer Learning: Knowledge of leveraging pre-trained models for solving real-world problems.

Participants will be assessed on:

Keras Framework Basics: Understanding the Keras API and model-building workflow.
Neural Network Construction: Ability to design and implement neural networks with Keras.
Data Preprocessing: Skills to preprocess and prepare data for deep learning models.
Model Evaluation: Proficiency in evaluating model performance using accuracy, loss functions, and validation techniques.
Transfer Learning: Ability to fine-tune pre-trained models for specific tasks.

Certificate of Completion: Participants who attend all sessions and successfully complete the course assessments will receive a ProgNXT Certificate of Completion for the Deep Learning with Keras Training Program.

Introduction to Deep Learning and Keras Basics

Introduction to Deep Learning and Keras

Overview of deep learning concepts and applications
Introduction to the Keras API: Simple vs Functional models
Installing and setting up Keras and TensorFlow
Practical exercise

Neural Network Basics

Understanding the architecture of neural networks: Layers, neurons, and weights
Activation functions: ReLU, sigmoid, and softmax
Loss functions and optimizers: MSE, categorical cross-entropy, Adam, and SGD
Practical exercise

Training and Evaluating Models

Training neural networks with Keras: Fitting, batch size, epochs
Model evaluation metrics: Accuracy, precision, recall, F1-score
Cross-validation and validation data usage
Practical exercise

Advanced Models and Real-World Applications

Convolutional Neural Networks (CNNs)

Introduction to CNNs and their applications in image recognition
Layers in CNNs: Convolution, pooling, and fully connected layers
Practical exercise: Building a CNN for image classification (e.g., CIFAR-10)

Recurrent Neural Networks (RNNs) and LSTMs

Understanding RNNs for sequence data processing
LSTMs and GRUs: Addressing long-term dependencies in data
Practical exercise

Transfer Learning with Keras

Understanding transfer learning and pre-trained models (e.g., VGG16, ResNet50)
Fine-tuning pre-trained models for custom tasks
Practical exercise

Model Deployment and Saving

Saving and exporting trained models in Keras
Using model.save() and tf.keras.models.load_model() for deployment
Practical exercise

Course Recap and Q&A Session

Recap of key concepts and techniques learned during the course
Q&A session to address any challenges or queries
Final thoughts on next steps in deep learning

Course slides and reference materials
Access to datasets and pre-configured Python notebooks
Practical code examples for hands-on exercises and model implementations

Participants will be evaluated through hands-on exercises, quizzes, and a final project.
ProgNXT Certificates of completion will be awarded to participants who successfully complete the course assessments.

Deep Learning with Keras Training Events in ontario

Online Events

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More Upcoming Session Dates

October 2026

📍 Ontario, Canada

18th Oct 2026→19th Oct 2026

🌐 Online Instructor-Led

22nd Oct 2026→23rd Oct 2026

November 2026

📍 Ontario, Canada

1st Nov 2026→2nd Nov 2026

🌐 Online Instructor-Led

6th Nov 2026→7th Nov 2026

📍 Ontario, Canada

19th Nov 2026→20th Nov 2026

🌐 Online Instructor-Led

23rd Nov 2026→24th Nov 2026

December 2026

🌐 Online Instructor-Led

3rd Dec 2026→4th Dec 2026

📍 Ontario, Canada

10th Dec 2026→11th Dec 2026

📍 Ontario, Canada

24th Dec 2026→25th Dec 2026

🌐 Online Instructor-Led

24th Dec 2026→25th Dec 2026

Events for other courses in Ontario, Canada

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Deep Learning with Keras Training in Ontario