GoLogica delivers its Generative AI Training Program in Toronto. The program provides instruction about Deep Learning, NLP, Prompt Engineering, Chat GPT, and Reinforcement Learning using TensorFlow and PyTorch. Learners in this course benefit from direct project work combined with real-world examples.
GoLogica Academic's Master Program features a structured curriculum, paving the way to Global scope.
Industry Experience
GoLogica having a 15+ years of experience on career transforming programs with industrial oriented Skills.
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Hands-on Experience
GoLogica emphasizes practical learning with exercises, projects to equip you with real world application.
Learners Achievement
Maximum Salary Hike
150%
Average Salary Hike
75%
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Generative AI Program Details
The Generative Al Training Course offered by GoLogica in Toronto delivers thorough education and practical experience in artificial intelligence together with Deep Learning, Machine Learning, and Prompt Engineering. The program helps you develop automated AI models that create human-simulated texts along with images, music, and visual outputs which drive transformations across content production and automation sectors.
The program begins by teaching the basic concepts of Artificial Intelligence and Machine Learning including Supervised and Unsupervised Learning together with Neural Networks and different Deep Learning Architectures. Understanding Python programming becomes vital because it forms the core requirement for building AI models in development.
The program mainly focuses on Natural Language Processing (NLP), which represents a primary research field to understand GPT, BERT, DALL.E, and LLMs. AI models are capable of understanding human text combined with the generation of natural language content to develop applications including chatbots, content generation tools, and translation systems.
The core aspect taught in this program is Prompt Engineering which stands as a scientific method for developing optimal inputs that boost artificial intelligence output quality. Learning to create prompts for LLMs like ChatGPT represents a key component of this program since it empowers AI to produce correct and contextually oriented responses for writing content, developing codes, handling customer inquiries and designing automated systems.
The program also explores Reinforcement Learning during which AI develops knowledge by conducting experiments. The program demonstrates autonomous learning models of AI which enable humans to make independent choices in robotics, gaming systems, and automated trading platforms.
The program stands out through its practical project work that demonstrates theoretical knowledge in real situations. You will construct artificial intelligence models throughout this program that replicate human creativity and intelligence through generative art and synthetic data creation, AI-powered chatbots as well as voice assistants.
The training program includes a practical project that enables learners to build a functioning generative AI system that exhibits their business application implementation skills in AI technology. The program provides you with adaptable online learning which includes recorded educational content, assignments as well as discussion platforms. The program also offers career support services such as resume building and interview preparation.
After completing this program graduates will be ready to work as AI Engineers, Data Scientists, Machine Learning Engineers, and AI Researchers. From GoLogica, you will obtain an industry-based certification that establishes your leadership in AI development, upon completion of the Generative AI Training Course in Toronto.
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Generative AI Syllabus
Python
Python was mainly developed for emphasis on code readability, and its syntax allows programmer to express concepts in fewer lines of code.Python is considered a scripting, language like Ruby or Perl and is often used for creating Web applications and dynamic Web content.
WEEK 5-6 20 Hours LIVE CLASS
History
Features
Setting up path
working with Python
Variable and Data Types
Operator
If
If- else
Nested if-else
For
While
Nested loops
Break
Continue
Pass
Accessing Strings
Basic Operations
String slices
Function and Methods
Accessing tuples
Operations
Working
Functions and Methods
Accessing list
Operations
Working with lists
Function and Methods
Defining a function
Calling a function
Types of functions
Function Arguments
Anonymous functions
Global and local variables
Importing module
Math module
Random module
Packages
Composition
Printing on screen
Reading data from keyboard
Opening and closing file
Reading and writing files
Functions
Exception
Exception handling
except clause
Try? Finally clause
User Defined Exceptions
Class and object
Attributes
Inheritance
Overloading
Overriding
Data hiding
Match function
Search function
Matching VS Searching
Modifiers
Patterns
Introduction
Architecture
CGI environment variable
GET and POST methods
Cookies
File upload
Connections
Executing queries
Transactions
Handling error
Socket
Socket Module
Methods
Client and server
Internet modules
GoLogica provides Data Science with Python Training This course has been designed with a focus on quality and simplicity making it ideal for Beginners or for those looking for a refresher on Data Science with Python. It gives an engaging learning experience covering everything you need to know about Data Science.
WEEK 7-8 30 Hours LIVE CLASS
Overview
Life Cycle of Data Science
MapReduce Framework
Importance of Data Science
Tools in Data Science
Need of Python in Data Science
Introduction
Terminologies of statistics
Measures of Centers & Spread
Types of distributions
Overview
Data Types and Variables
Operators
if Statements and lops
Functions in R
Introduction
ML Fundamentals
Learning Technologies
Decision Tree
Random forest classifiers
Deep Learning
Time Series Analysis
ChatGpt
In this course, you will learn about the workings of OpenAI’s ChatGPT model, the model architecture, and the fine-tuning techniques. You will also discover in detail how to embed ChatGPT into various applications, control conversation flows, and fine-tune it for distinct tasks. Applied, you’ll learn about the operative utilization and development of AI chatbots as well as NLP, making ChatGPT your robust tool in AI capability.
WEEK 3-4 12 Hrs LIVE CLASS
What is Chat GPT?
Understanding the capabilities and limitations
Use cases and applications
Setting up the environment
Choosing a development platform
Accessing the API or using the local runtime
Formatting your input
Sending requests to the model
Handling responses
Exploring different input formats
Prompts and instructions
System and user messages
Controlling response length
Adjusting temperature and top-k sampling
Maintaining context
Multi-turn conversations
Conversation history and context management
Resolving ambiguity and clarifying queries
Introduction to fine-tuning
Preparing your dataset
Training your fine-tuned model
Evaluating and deploying your model
Writing effective prompts and instructions
Managing bias and controversial topics
Handling sensitive information and user privacy
Ensuring safety and avoiding harmful outputs
Chat GPT API advanced features
Using system-level instructions for better control
Handling rare and out-of-distribution queries
Incorporating user feedback for model improvement
Prompt Engineering
The GoLogica Prompt Engineering Course is centered around effective prompts as a means to elicit the correct responses from AI models, together with ChatGPT. This course helps you learn when and how to write great prompts that obtain clear and relevant information. You will also learn how to better tune prompts to allow for an improved fit of the prompts to the task, thereby making ChatGPT and similar systems better suited for so many applications.
Week 4-5 15 Hours LIVE CLASS
What is Prompt Engineering, and why do we care?
English as a new programming language
Getting to know our GPT-based AI tool
The Naive Prompting Approach and the Persona Pattern
The Interview Pattern
The Chain-of-Thought Approach in Prompt Engineering
The Tree-of-Thought Approach in Prompt Engineering
Controlling Verbosity and the Nova System
Getting to Know watsonx Prompt Lab
Generative AI
The Generative AI Industry Applications course is built for understanding how innovative forms of AI, like the GPT, are transforming industries such as technology, entertainment, and production. You will get to understand how you can incorporate AI in automating tasks, creating content, and improving decision-making. This course enables students to apply the concepts in the project and case-study scenarios where generative AI can be of immense value.
WEEK 5-6 20 Hrs LIVE CLASS
1. Introduction to Generative AI
• Overview of Generative AI
• Real-World Applications (Art, Text, Audio, Video, Code Generation)
• Ethical Considerations in Generative AI (Bias, Deepfakes, Intellectual Property)
2. Mathematical and Statistical Foundations
• Linear Algebra (Matrix Multiplications, Singular Value Decomposition)
• Probability and Information Theory (KL Divergence, Entropy)
• Optimization Techniques (Gradient Descent, L-BFGS)
3. Programming and Tools for Generative AI
• Python Basics for Generative AI
• Libraries: TensorFlow, PyTorch, Hugging Face Transformers
4. Hands-on Exercise 1
• Implement a simple random noise generator using NumPy.
• GAN Architecture (Generator, Discriminator)
• Loss Functions in GANs (Minimax, Wasserstein Loss)
• Challenges in Training GANs (Mode Collapse, Vanishing Gradients)
7. Hands-on Project 1
• Build a sim/x.ple GAN to generate handwritten digits (MNIST Dataset).
8. Transformers and Attention Mechanisms
• Attention is All You Need: Transformer Basics
• Pretrained Models (BERT, GPT, T5)
• Fine-tuning Generative Transformers for Tasks (e.g., Text Completion, Summarization)
• Normalizing Flows (RealNVP, Glow)
• Density Estimation and Sampling
11. Hands-on Project 2
• Implement a text generation model using GPT or similar transformer architecture.
12. Vision-Language Models
• CLIP: Connecting Text and Images
• DALL•E and Stable Diffusion
13. Audio and Speech Generation
• Text-to-Speech (TTS) Models (Tacotron, WaveNet)
• Music Generation with RNNs or Transformers
14. Video and Animation
• Video Synthesis Techniques
• Applications in Game Development and Media
15. Hands-on Project 3
• Create a multimodal model to generate images based on text prompts (e.g., leveraging Stable Diffusion).
15. Prompt Engineering for Generative Models
• Fundamentals of Prompt Design
• Crafting Effective Prompts for AI Models
• Advanced Prompting Techniques (Zero-Shot, Few-Shot, Chain-of-Thought)
• Practical Use Cases (Chatbots, Summarization, Knowledge Extraction)
• Understanding How Generative Models Interpret Prompts
• Techniques for Text-to-Image Prompts (e.g., DALL•E, Stable Diffusion)
• Experimenting with Text-to-Text Prompts (e.g., GPT Models)
• Crafting Prompts for Multimodal AI (e.g., CLIP, Audio Generation)
19. Hands-on Activity
• Experiment with prompts in GPT-based models to perform specific tasks (e.g., creative writing, data extraction).
16. Hands-on Activity
• Create and refine prompts to generate high-quality outputs for text, image, and multimodal systems.
16. Optimization Techniques
• Fine-Tuning and Transfer Learning for Generative AI Models
• Model Compression for Deployment (Pruning, Quantization)
17. AI Deployment for Generative Models
• Deploying Models via APIs (FastAPI, Flask)
• Scaling with Cloud Platforms (AWS, Azure, GCP)
18. Hands-on Project 4
• Deploy a generative model as a web application with a user-friendly interface.
19. Ethics in Generative AI
• Risks of Generative Models (Deepfakes, Misuse of Content)
• Responsible Use and Fairness in AI
20. Regulation and Policies
• Current Regulations around Generative AI
• Understanding Copyright and Data Privacy Implications
21. Hands-on Discussion
• Group debate or case study analysis on the ethical challenges of generative AI.
22. Capstone Project
• Design, build, and deploy a comprehensive generative AI system (e.g., content generator, creative AI tool).
23. Portfolio and Resume Development
• Showcasing Projects and Contributions
• Publishing Work (GitHub, Kaggle, Personal Website)
24. Mock Interviews and Career Guidance
• Technical and Behavioral Interview Preparation
• Networking Strategies and Career Paths in Generative AI
To become a master in Generative AI?
Skills Covered
Tools Covered
Career Support
Personalized Industry Session
This will help you to better understand the Generative AI.
High-Performance Coaching
you will be able to grow your career by broadening your proficiency in Generative AI.
Career Mentorship Sessions
With this, the students will be able to decide their careers in the right way.
Interview Preparation
We Help with face-to-face interaction through mock interviews & Exams
Program Fee
Program Fee: 98000 /-
88200 /-
Discount: 9800
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UPI
Generative AI Certification
GoLogica Generative AI Certification holds accreditation from major global companies worldwide. Upon completion of both theoretical and practical sessions, we offer certification to both freshers and corporate trainees. Our certification on Generative AI is recognized globally through GoLogica, significantly enhances the value of your resume, opening doors to prominent job positions within leading MNCs. Attainment of this certification is contingent upon the successful completion of our training program and practical projects.
Job Outlook
Personalized Industry Session
The U.S. Bureau of Labor Statistics (BLS) forecasts a 25% increase in employment for Generative AI from 2021 to 2031, significantly outpacing the average for all occupations. Additionally, Generative AI Ventures predicts 3.5 million unfilled cybersecurity jobs worldwide by 2025.
High-Performance Coaching
According to the BLS, Generative AI professionals are well-compensated. The median annual wage for Generative AI was $120,000 and $180,000 PA It’s depending on factors such as experience, location, and specific job responsibilities.
Job Titles
Are you preparing for a interview? If yes, our expert tutors will help you with this.
Machine Learning Engineer
AI Engineer
Data Scientist
NLP Engineer
Generative AI Researcher
Prompt Engineer
Generative AI Faq’s
The program generally takes anywhere from 6 to 7 months to complete, depending on the speed of the learner and category of learning, full-time or part-time.
The program offers a combination of real-time instructor-led and recorded modular and asynchronous designs.
Yes, you will receive a Generative AI Master’s Program certificate from GoLogica.
No, it is not necessary to have prior experience in using artificial intelligence technologies.
With this program, you will learn popular AI skills, receive individualized job search assistance, and find the most attractive positions for working in the AI sector.
You will apply AI in practice throughout the entire course, creating conversational agents, deploying AI models, and applying AI to selected industry issues.
You can apply for some job positions like AI Engineer, Machine Learning Engineer, NLP Specialist, Data Scientist, and Prompt Engineer.
The average salaries of AI engineers can cost around 12 lakhs per annum in India.
Prompt engineering refers to creating suitable prompts for attaining the right results from an AI model such as ChatGPT. This part is an important step when it comes to achieving the best performance levels of AI models.
No, it is not necessary. However, having a background in data science is an advantage.
This program is concentrated mainly on Generative AI models as well as their practical usage, providing the best approaches to comprehending the newest trends in AI systems such as ChatGPT and Prompt Engineering.
Learners receive instant technical assistance, the possibility of learning directly from AI specialists, and project and assignment assistance.
Basic programming knowledge, preferably in Python, is recommended. Familiarity with data science concepts will be useful.
You will have access to live sessions, recorded tutorials, study materials, project workbooks, and a peer community for collaboration and networking.
Yes, you can attend pre-recorded sessions and complete assignments at your convenience. However, live sessions are scheduled and should be attended in real time.
Yes, you will be able to access all recorded sessions and course materials after the program.
Generative AI is widely used in industries such as finance, entertainment, marketing, and manufacturing for tasks such as content creation, automation, and decision-making.
Yes, GoLogica does offer guaranteed job placement assistance, which includes writing CVs, conducting interviews, and offering genuine job links.
Yes, the program is flexible. It offers part-time learning options with pre-recorded videos and weekend live sessions.
You will be given constant career advice, high-performance counseling, and multiple opportunities to get in touch with professionals who assist users with their job search and interviews.
You will follow how AI can be applied in the following fields: natural language processing (NLP), healthcare automation, finance, and writing.
You can register from the GoLogica official website and choose the Generative AI Master’s Program to register for the course.
The program is also available for international students. Both lectures and all the teaching materials are available online.
Yes, there are coding assignments, as integration with programming is a part of the program, mainly in Python and machine learning.
Your lab will include programming in Python, Tensorflow, or any model developed by OpenAI like ChatGPT, Natural language Processing frameworks like NLP, etc.
Yes, there are various quizzes and individual and group project check-ups that tell you if you’re on track in meeting the learning objectives.
Yes, you can slow down or speed up according to your preference, but the restrictions are well spelled out to switch between part-time and full time; you will have to contact the support team to discuss this.
Indeed, our program is crowned with a capstone project during which you will implement generative AI in practice to address a specific challenge.
In case you missed yesterday’s live, you can always watch the recorded version to get the necessary information.
The growth in demand for AI professionals is almost constant, and the successful completion of this program means one will be qualified to advance in any particular field in terms of Artificial Intelligence.
