Generative AI Training Course by Tonex

Generative AI Training is a 2-day course where participants learn from experienced instructors who are experts in generative AI. Participants will also have access to a wealth of resources, including a forum, a library, and a job board.

Generative AI uses a number of techniques that continue to evolve, but foremost are AI foundation models.

Generative AI foundation models are trained on a broad set of unlabeled data that can be used for different tasks, with additional fine-tuning. Complex math and enormous computing power are required to create these trained models, but they are, in essence, prediction algorithms.

What separates generative AI from AI in general is that generative AI can learn from existing artifacts to generate new, realistic artifacts (at scale) that reflect the characteristics of the training data but don’t repeat it.

Consequently, generative AI can produce a variety of novel content, such as images, video, music, speech, text, software code and product designs.

Even though generative AI is still somewhat in the “discovery stages,” businesses have already begun to put this innovative technology to good use.

One of the current generative AI use cases in business revolves around providing instant responses to customer inquiries received via live chat, phone calls, and emails. In addition to fully automating customer service, businesses can tap into generative AI to augment the work of human specialists.

Some businesses have also turned to extreme personalization of customer service as another way to use generative AI in business.

By analyzing subtle patterns in call recordings, such as word choices, speech rate, and tone of voice, generative AI can help organizations adjust communications and come up with tailored offerings to improve customer engagement and loyalty.

The business process automation (BPA) landscape is also turning to generative AI. Compared to rule-based or even regular AI-infused BPA tools, generative AI business applications are broader and more complex. Their transformational power comes from generative AI’s capacity to comprehend natural language.

According to McKinsey, using generative AI in business strategically can automate up to 70% of tasks that take up your employees’ time. This can lead to a notable increase in productivity, with a yearly improvement rate of 3.3%.

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