Generative AI Introduction and Overview

Generative AI Introduction and Overview.

The "Generative AI: Introduction and Overview" learning provides an introduction to the field of Generative AI. Beginning with the basics, learners will explore the applications, key concepts, and deep learning techniques of Generative AI, progressing towards more complex topics like advanced methodologies and ethical issues. The series ends in a practical project where learners can apply their acquired knowledge to build a Generative AI model, providing a hands-on experience that reinforces theoretical learning.
Designed to cater to a diverse range of learners, this educational journey is ideal for anyone from data scientists and IT managers to newcomers in the AI field across different geographies. This journey is suited for professionals looking to deepen their understanding of Generative AI and leverage its capabilities within their respective industries, enhancing both their personal and organizational growth.

This Learning Kit with more than 11 hours of learning is divided into three tracks:

Course content

Track 1: Generative AI Overview

In this track, the focus will be on applications, key concepts, and deep learning techniques of Generative AI, progressing towards more complex topics like advanced methodologies and ethical issues. The series ends in a practical project where learners can apply their acquired knowledge to build a Generative AI model, providing a hands-on experience that reinforces theoretical learning.

An Introduction to Generative AI

Course: 1 Hour, 41 Minutes

• Course Overview
• What Is Generative AI?
• Content Generation Using Generative Models
• Prompt Engineering
• Evolution of Generative AI
• Recent Advances in Generative AI
• Applications of Generative AI
• Generative AI Risks
• Ethical Considerations in Working with Generative AI
• Deepfake AI
• Course Summary

Generative AI Models: Getting Started with Autoencoders

Course: 2 Hours, 15 Minutes

• Course Overview
• Autoencoders for Representation Learning
• Autoencoder Architectures
• Setting up the Google Colab Environment
• Downloading and Exploring the Fashion MNIST Dataset
• Configuring the Autoencoder Architecture
• Training the Autoencoder and Visualizing Reconstructions
• Training Convolutional Autoencoders
• Reconstructing Multichannel Images with DNN Autoencoders
• Reconstructing Multichannel Images with CNN Autoencoders
• The Denoising Autoencoder
• Configuring and Training Denoising Autoencoders
• The Sparse Autoencoder
• Course Summary

Generative AI Models: Generating Data Using Variational Autoencoders

Course: 1 Hour, 18 Minutes

• Course Overview
• Variational Autoencoders
• Variational Autoencoder Implementation
• Setting up the Variational Autoencoder
• Training a Variational Autoencoder
• Training a VAE Using Convolutional Networks
• Training VAEs on Multichannel Images
• Course Summary

Generative AI Models: Generating Data Using Generative Adversarial Networks

Course: 1 Hour, 40 Minutes

• Course Overview
• Generative Adversarial Networks (GANs)
• Generative Adversarial Network Training
• Setting up a Virtual Environment for GAN Training
• Loading and Exploring the MNIST Dataset
• Creating a Generator and a Discriminator
• Training a Generative Adversarial Network
• Deep Convolutional Generative Adversarial Networks (DCGANs)
• Loading and Exploring the CelebFaces Dataset
• Training a DCGAN
• Course Summary

Using OpenAI APIs: Exploring APIs with the OpenAI Playground

Course: 1 Hour, 45 Minutes

• Course Overview
• Introduction to Generative AI and Large Language Models (LLMs)
• ChatGPT and the OpenAI Playground
• OpenAI Application Programming Interfaces (APIs)
• Exploring OpenAI APIs and Pricing
• Getting Started with the OpenAI Playground
• Assigning Personas and Tweaking Creativity
• Using the Legacy Completions API via the Playground
• Exploring OpenAI Prompt Examples
• Creating an OpenAI Assistant
• Querying the OpenAI Assistant
• Course Summary

Using OpenAI APIs: Accessing OpenAI APIs from Python

Course: 1 Hour, 53 Minutes

• Course Overview
• Generating Application Programming Interface (API) Keys to Use with Endpoints
• Making API Requests with cURL
• Making Our First API Request Using Python
• Exploring Chat Completions and JSON Mode
• Streaming Chat Completions with the Legacy Completions API
• Exploring Chat and Completion Models
• Setting up Utility Functions to Explore Model Determinism
• Using the Seed Parameter for Almost Deterministic Responses
• Tweaking Model Parameters – Temperature and Max Tokens
• Tweaking Model Parameters – Stop Sequences Top P and Penalties
• Course Summary

Using OpenAI APIs: Using Image & Audio APIs

Course: 1 Hour, 13 Minutes

• Course Overview
• Generating Images Using DALL-E Models
• Working with Image Variations and Inpainting
• Performing Audio Transcription
• Performing Translation and Text-to-Speech Conversion
• Evaluating Transcribed Audio
• Installing and Using the Whisper Model Locally
• Using Chat Completions to Interpret Images
• Course Summary

Using OpenAI APIs: Fine-tuning Models, the Assistants API, & Embeddings

Course: 1 Hour, 23 Minutes

• Course Overview
• Setting up Prompt Completion Pairs for Fine-tuning
• Creating and Executing a Fine-tuning Job
• Viewing Chat Responses from Fine-tuned Models
• Creating Assistants Programmatically
• Uploading Files to Assistants
• Creating and Using Functions to Interact with Assistants
• Creating Embeddings for Text Data
• Clustering Text Using Word Embeddings
• Classifying Reviews Using Word Embeddings
• Course Summary

Assessment:

• Final Exam: Generative AI Introduction and Overview

Specificaties

Taal: Engels
Kwalificaties van de Instructeur: Gecertificeerd
Cursusformaat en Lengte: Lesvideo's met ondertiteling, interactieve elementen en opdrachten en testen
Lesduur: 11:38 uur
Assesments: De assessment test uw kennis en toepassingsvaardigheden van de onderwerpen uit het leertraject. Deze is 365 dagen beschikbaar na activering.
Online Virtuele labs: Ontvang 12 maanden toegang tot virtuele labs die overeenkomen met de traditionele cursusconfiguratie. Actief voor 365 dagen na activering, beschikbaarheid varieert per Training.
Online mentor: U heeft 24/7 toegang tot een online mentor voor al uw specifieke technische vragen over het studieonderwerp. De online mentor is 365 dagen beschikbaar na activering, afhankelijk van de gekozen Learning Kit.
Voortgangsbewaking: Ja
Toegang tot Materiaal: 365 dagen
Technische Vereisten: Computer of mobiel apparaat, Stabiele internetverbindingen Webbrowserzoals Chrome, Firefox, Safari of Edge.
Support of Ondersteuning: Helpdesk en online kennisbank 24/7
Certificering: Certificaat van deelname in PDF formaat
Prijs en Kosten: Cursusprijs zonder extra kosten
Annuleringsbeleid en Geld-Terug-Garantie: Wij beoordelen dit per situatie
Award Winning E-learning: Ja

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