Generative AI on Coursera Lectures

Genenerative AI Course

AI for Business

• AI Fundamentals for Non-Data Scientists
• AI Applications in Marketing and Finance
• AI Applications in People Management
• AI Strategy and 구

AI for Good

• Master a step-by-step framework for the development of AI projects
• Explore real-world case studies related to public health, climate change, and disaster management
• Analyze data and build AI models for projects focused on air quality, wind energy, biodiversity monitoring, and disaster management

Google AI

• Google Cybersecurity
  • Understand the importance of cybersecurity practices and their impact for organizations
  • Identify common risks, threats, and vulnerabilities, as well as techniques to mitigate them
  • Protect networks, devices, people, and data from unauthorized access and cy berattacks using Security Information and Event Management (SIEM) tools
  • Gain hands-on experience with Python, Linux, and SQL
• Introduction to Generative AI
  • Define Generative AI
  • Explain how generative AI works
  • Describe generative AI model types
  • Describe generative AI applications
• Introduction to generatiev AI studio
  • Explain what generative AI studio does
  • Describe generative AI studio options
  • Use the generative AI language tool
• Attention mechanism
  • Understand the concept of attention and how it works
  • Learn how attention mechanism is applied to machine translation
• Create Image Cpationing Models
  • Understand the different components of an image captioning model
  • Learn how to train and evaluate an image captioning model
  • Use your image captioning models to generate captions for images
• Encoder-Decoder Architecture
  • Understand the main components of the encoder-decore architecture
  • Learn how to train and generate text from a model by using the encoder-decoder architecture
  • Learn how to write your own encoder-decoder model in keras
• Introduction to Large Language Models
  • Define Large Language Models (LLMs)
  • Describe LLM Use Cases
  • Explain Prompt Tuning
  • Describe Google’s Gen AI Development Tools
• Introduction to Responsible AI
  • Understand why Google has put AI principles in place
  • Identify the need for a responsible AI practice within an organization
  • Recognize that decisions made at all stages of a project have an impact on responsible AI
  • Recognize that organizations can design AI to fit their own business needs and values
• Transformer Models and BERT model
  • Understand the main components of the Transformer architecture
  • Learn how a BERT model is built using Transformers
  • Use BERT to solve differnt natural language processing (NLP) tasks

Cybersecurity Foundations for Risk Management

• Define key concepts and terminology in Cybersecurity
• Identify threats to cybersecurity
• Describe the role and responsibilites of Cybersecurity management in the risk management effort
• Explain Cybersecurity risk and the organizational program to manage it

Generative Adversarial Networks (GANs)

• Understand GAN components, build basic GANs using PyTorch and advanced DCGANs using convolutional layers, control your GAN and build conditional GAN
• Compare generative models, use FID method to assess GAN fidelity and diversity, learn to detect bias in GAN, and implement StyleGAN techniques
• Use GANs for data augmentation and privacy preservation, survey GANs appliations, and examine and build Pix2Pix and CycleGAN for image translation

Generative AI Fundamentals IBM

• Explain the fundamental concepts, capabilities, models, tools, applications, and patforms of generative AI foundation models.
• Apply powerful prompt engineering techniques to write effective prompts and generate desired outcomes from AI models
• Discuss the limitations of generative AI and explain the ethical concerns and considerations for the responsible use of generative AI
• REcognize the ability of generative AI to enhance your career and help implement improvements at your workplace

Generative AI for Everyone

• What generative AI is and how it works, its common use cases, and what this technology can and cannot do
• How to think through the lifecycle of a generative AI project, from conception to launch, including how to build effective prompts.
• The potential opportunities and risks that generative AI technologies present to individuals, businesses, and society.

Generative AI for Learders

• Using generative AI in leadership
• generative AI
• prompt engineering for leaders

Generative AI with Large Language Models

• Gain foundational knowledge, practical skills, and a funtional understanding of how generative AI works
• Dive into the latest research on Gen AI to understand how companies are creating value with cutting-edge technology
• Instruction from expert AWS AI practitioners who actively build and deploy AI in business use-cases today
• LLMs