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  • Generative Ai

Build Generative AI Skills with Projects

Generative AI projects can help you learn how to apply model fundamentals to hands-on work, from designing prompts to building simple generation workflows. You can build skills in model evaluation, data preparation, and refining outputs for specific goals. Many courses introduce tools such as Python libraries or low-code interfaces that support creating, testing, and iterating on generative AI projects.


Full List of Generative AI Projects


  • C

    Coursera

    Generative AI with Vertex AI: Build a customer chatbot

    Skills you'll gain: Cloud API, Google Cloud Platform, Text Mining, Application Programming Interface (API), LLM Application, Generative AI, Natural Language Processing, Jupyter, Python Programming, Classification Algorithms

    4.1
    Rating, 4.1 out of 5 stars
    ·
    7 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Prompt Engineering Generative AI for Marketing & Advertising

    Skills you'll gain: Prompt Engineering, Generative AI, A/B Testing, Copywriting, Advertising, Marketing, ChatGPT, Content Creation, Marketing Strategies, Marketing Analytics, Customer Insights, Social Media Content

    4.5
    Rating, 4.5 out of 5 stars
    ·
    107 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • D

    Duke University

    Introduction to Retrieval Augmented Generation (RAG)

    Skills you'll gain: Retrieval-Augmented Generation, Vector Databases, Embeddings, OpenAI API, Data Import/Export, Pandas (Python Package), Generative AI, Application Programming Interface (API), Data Manipulation, Large Language Modeling, Python Programming, Machine Learning

    4.4
    Rating, 4.4 out of 5 stars
    ·
    48 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    GenAI For Business Analysis: Fine-Tuning LLMs

    Skills you'll gain: Model Evaluation, OpenAI API, Data Preprocessing, OpenAI, Large Language Modeling, Real Time Data, Data Manipulation, Generative AI, Python Programming, Unstructured Data, Performance Metric, Machine Learning, JSON

    4.4
    Rating, 4.4 out of 5 stars
    ·
    11 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    D

    Duke University

    GenAI Basics - How LLMs Work

    Skills you'll gain: Large Language Modeling, Generative AI, Machine Learning, Applied Machine Learning, Artificial Intelligence, Data Science

    3.9
    Rating, 3.9 out of 5 stars
    ·
    37 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    OpenAI for Beginners: AI Assistants for Project Managers

    Skills you'll gain: No-Code Development, Generative AI, AI Product Strategy, Application Deployment, LLM Application, AI Enablement, OpenAI, Project Management, Prompt Engineering

    3.7
    Rating, 3.7 out of 5 stars
    ·
    31 reviews

    Beginner · Guided Project · Less Than 2 Hours

What brings you to Coursera today?

  • Status: Free
    Free
    M

    Microsoft

    Build a computer vision app with Azure Cognitive Services

    Skills you'll gain: Application Programming Interface (API), Microsoft Azure, Cloud API, Computer Vision, Artificial Intelligence and Machine Learning (AI/ML), User Accounts, Image Analysis, Artificial Intelligence, Cloud Computing, Software Development

    4.5
    Rating, 4.5 out of 5 stars
    ·
    521 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Business Analysis & Process Management

    Skills you'll gain: Process Analysis, Business Process, Business Analysis, Workflow Management, Process Management, Process Flow Diagrams, Business Process Modeling, Stakeholder Management, Stakeholder Analysis, Computer Literacy

    4.5
    Rating, 4.5 out of 5 stars
    ·
    7.4K reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Midjourney for Beginners: Craft an Exquisite Piece of AI Art

    Skills you'll gain: 3D Assets, Generative AI, Prompt Engineering, Digital Design, Graphics Software, Creativity, Design and Product, Marketing Design

    4.1
    Rating, 4.1 out of 5 stars
    ·
    24 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Github CoPilot for Beginners: Write Software With AI

    Skills you'll gain: Responsive Web Design, HTML and CSS, Web Design and Development, UI Components, Prompt Engineering, Web Development Tools, Web Development, Generative AI, Javascript, Software Engineering, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    74 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Perplexity.AI for Beginners: AI-Powered Search

    Skills you'll gain: Prompt Engineering, AI Enablement, Technical Communication, Artificial Intelligence, Information Architecture, User Interface (UI)

    3.5
    Rating, 3.5 out of 5 stars
    ·
    19 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Deep Learning with PyTorch : Generative Adversarial Network

    Skills you'll gain: Generative Adversarial Networks (GANs), PyTorch (Machine Learning Library), Deep Learning, Convolutional Neural Networks, Image Analysis, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    99 reviews

    Intermediate · Guided Project · Less Than 2 Hours

1234…12

In summary, here are 10 of our most popular generative ai courses

  • Generative AI with Vertex AI: Build a customer chatbot: Coursera
  • Prompt Engineering Generative AI for Marketing & Advertising: Coursera
  • Introduction to Retrieval Augmented Generation (RAG): Duke University
  • GenAI For Business Analysis: Fine-Tuning LLMs: Coursera
  • GenAI Basics - How LLMs Work: Duke University
  • OpenAI for Beginners: AI Assistants for Project Managers: Coursera
  • Build a computer vision app with Azure Cognitive Services: Microsoft
  • Business Analysis & Process Management: Coursera
  • Midjourney for Beginners: Craft an Exquisite Piece of AI Art: Coursera
  • Github CoPilot for Beginners: Write Software With AI: Coursera

Frequently Asked Questions about Generative Ai

Generative AI refers to a subset of artificial intelligence that focuses on creating new content, whether it be text, images, music, or other forms of media. This technology is important because it has the potential to revolutionize various industries by automating creative processes, enhancing productivity, and enabling personalized experiences. As businesses increasingly adopt generative AI, understanding its capabilities and applications becomes crucial for anyone looking to stay relevant in the job market.‎

Careers in generative AI are diverse and growing rapidly. You can explore roles such as AI Engineer, Data Scientist, Machine Learning Engineer, and Software Developer, among others. Additionally, positions like AI Product Manager and Generative AI Consultant are emerging as organizations seek professionals who can effectively integrate this technology into their operations. The demand for skilled individuals in this field is expected to continue rising, making it a promising area for career development.‎

To succeed in generative AI, you should develop a strong foundation in programming languages such as Python or Java, as well as a solid understanding of machine learning concepts. Familiarity with AI frameworks and tools, such as TensorFlow or PyTorch, is also beneficial. Additionally, skills in data analysis, natural language processing, and creative thinking will enhance your ability to work with generative AI technologies effectively.‎

There are several excellent online courses available for learning about generative AI. For instance, the AWS Generative AI Applications Professional Certificate provides practical insights into applying generative AI in real-world scenarios. Another option is the IBM Generative AI Engineering Professional Certificate, which focuses on engineering aspects. These courses can help you build a solid understanding of generative AI principles and applications.‎

Yes. You can start learning generative AI on Coursera for free in two ways:

  1. Preview the first module of many generative AI courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in generative AI, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn generative AI, start by identifying your learning goals and the specific areas of interest within the field. Enroll in online courses that match your objectives, such as those focusing on programming, machine learning, or specific applications of generative AI. Engage with hands-on projects to apply what you learn, and consider joining online communities or forums to connect with others in the field. Consistent practice and exploration will help you build confidence and expertise.‎

Generative AI courses typically cover a range of topics, including the fundamentals of machine learning, neural networks, and natural language processing. You may also learn about specific generative models, such as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders). Additionally, courses often explore practical applications, ethical considerations, and the integration of generative AI into various industries.‎

For training and upskilling employees, courses like the Generative AI for Software Development Skill Certificate and the Microsoft 365 with Generative AI Professional Certificate are excellent choices. These programs focus on practical skills and applications, making them suitable for organizations looking to enhance their workforce's capabilities in generative AI.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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