Generative AI Training Course by Tonex
Generative AI Training is a 2-day course for beginner and intermediate learners. Participants learn about topics such as generative modeling techniques, deep learning frameworks, and applications of generative AI in various fields, such as healthcare, finance, and entertainment.
Generative AI Training is a 2-day course where participants experience a comprehensive and affordable education into the fundamentals of generative AI technology, what it can do and what the future likely holds.
Generative AI is sometimes referred to as the next productivity frontier.
The latest generative AI applications can perform a range of routine tasks, such as the reorganization and classification of data as well as the ability to write text, compose music, and create digital art.
Cutting-edge applications such as these have made headlines and persuaded consumers and households to experiment on their own. As a result, a broader set of stakeholders are grappling with generative AI’s impact on business and society.
But the discovery of generative AI technology is just beginning. Studies suggest that generative AI is poised to transform roles and boost performance across functions such as sales and marketing, customer operations, and software development.
In the process, generative AI applications could unlock trillions of dollars in value across sectors from banking to life sciences.
One of the most popular applications of generative AI is within the realm of images.
Generative AI models can create graphs that show new chemical compounds and molecules that aid in drug discovery, create realistic images for virtual or augmented reality, produce 3D models for video games, design logos, enhance or edit existing images, and more.
Generative AI technology is also coming up big in language applications. Text is at the root of many generative AI models and is considered to be the most advanced domain. For example, large language models (LLMs) are being leveraged for a wide variety of tasks, including essay generation, code development, translation, and even understanding genetic sequences.
Additionally, synthetic data is useful to train AI models when data doesn’t exist, is restricted, or is simply unable to address corner cases with the highest accuracy.
This is a major breakthrough. The development of synthetic data through generative models is perhaps one of the most impactful solutions for overcoming the data challenges of many enterprises. It spans all modalities and use cases and is possible through a process called label efficient learning.
Generative AI Training Course by Tonex
Generative AI Training by Tonex is a comprehensive course that covers the fundamentals of generative AI, including Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL). The course is designed for beginners and intermediate learners, and it provides a solid foundation in the principles of generative AI. Participants will also learn about ChatGPT and OpenAI ChatGPT API, which allows developers to integrate ChatGPT into their own applications, including websites.
The course begins with an introduction to generative AI, and it then covers the topics like, Natural language processing, Machine learning and Deep learning. The course also includes a number of hands-on projects that allow learners to apply the concepts they have learned.
Key Benefits:
Attending a Generative AI training program can offer several benefits. Here are a few reasons why you might want to attend such a program:
- You will learn from experienced instructors who are experts in generative AI.
- You will have access to a wealth of resources, including a forum, a library, and a job board.
Learning Objectives:
Upon completion of this course, participants are able to:
- Learn the fundamentals of generative AI and its applications.
- Explain various generative AI models and algorithms.
- Develop skills to implement and train generative AI models.
- Learn techniques for evaluating and improving generative AI models.
- Explore advanced topics in generative AI, such as conditional generation, style transfer, and text-to-image synthesis.
- Apply generative AI techniques to real-world problems and creative applications.
- Explore ethical considerations and challenges associated with generative AI.
Why Choose “Generative AI” Course by Tonex?
There are many reasons to choose Tonex for your generative AI training. Here are just a few:
- Expert instructors: Tonex instructors are experts in generative AI with years of experience in the field. They are passionate about teaching and are committed to helping you succeed.
- Comprehensive curriculum: Tonex’s curriculum is comprehensive and covers all the essential topics in generative AI. You will learn from the ground up and be well-prepared to apply your skills in the real world.
- Hands-on projects: Tonex’s courses are project-based, which means you will have the opportunity to apply what you learn in real-world scenarios. This will help you solidify your understanding of the material and make you more marketable to employers.
- Flexible learning options: Tonex offers a variety of learning options, so you can choose the one that best suits your needs. You can take our courses online, in person, or blended.
If you are looking for a comprehensive and affordable generative AI training program, then Tonex is the right choice for you. Contact us today to learn more about our courses and to get started on your learning journey.
Who Should Attend?
Generative AI Training by Tonex is a great course for anyone who wants to learn about generative AI. The course is designed for beginners and intermediate learners, so it is suitable for people with a variety of backgrounds. Some of the people who would benefit from attending this course include:
- Software developers
- Data scientists
- Business professionals
- Anyone interested in learning about generative AI.
Learn the topics such as generative modeling techniques, deep learning frameworks, and applications of generative AI in various fields, such as healthcare, finance, and entertainment.
Course Outline:
Introduction to Generative AI
- What is generative AI?
- History of generative AI
- Applications of generative AI
- Fundamentals of ChatGPT
- Overview of generative AI models: GANs, VAEs, autoregressive models
Introduction to Machine Learning
- What is machine learning?
- Supervised learning
- Unsupervised learning
- Reinforcement learning
Introduction to Deep Learning
- What is deep learning?
- Neural networks
- Convolutional neural networks
- Recurrent neural networks
Fundamentals of Natural Language Processing (NLP)
- What is natural language processing?
- Tokenization
- Stemming
- Lemmatization
- Part-of-speech tagging
Fundamentals of Generative Models
- Probability theory and generative modeling
- Maximum likelihood estimation
- Latent space and latent variable models
- Generative Adversarial Networks (GANs)
- GAN architecture and components
- Training GANs: minimax game and adversarial training
- GAN variants: DCGAN, WGAN, CycleGAN
- Variational Autoencoders (VAEs)
- Autoencoders and variational inference
- Conditional generation with VAEs
- Autoregressive Models
- PixelCNN and PixelRNN
- Transformers for generative modeling
Evaluating and Improving Generative Models
- Metrics for evaluating generative models
- Challenges and techniques for improving model performance
- Understanding and mitigating mode collapse
Advanced Topics in Generative AI
- Conditional generation and controllable synthesis
- Style transfer and image-to-image translation
- Text-to-image synthesis and image captioning
- Ethical Considerations in Generative AI
- Bias and fairness in generative models
- Intellectual property (IP) and copyright issues
- Privacy concerns and data ethics
- Future Directions and Wrap-up
Hands-on Projects
- Integrating Building a chatbot
- Generating text
- Translating languages
- Writing different kinds of creative content
- OpenAI ChatGPT API
- Integrate ChatGPT into your own applications, including websites, mobile apps, productivity software and more.
- Integration of Generative AI and Trusted AI