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Steve Ballinger, MBA

Unlock the power of Artificial Intelligence (AI) and dive deep into the exciting world of Generative AI with this comprehensive course designed for beginners and enthusiasts alike. In this course, you'll explore the foundations of AI, understand how it differs from regular computer programs, and learn the essential concepts behind generative models. Whether you’re curious about AI’s impact, want to enhance your professional skillset, or simply explore the latest trends, this course will equip you with the knowledge you need to thrive in today’s AI-driven world.

What You'll Learn:

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Unlock the power of Artificial Intelligence (AI) and dive deep into the exciting world of Generative AI with this comprehensive course designed for beginners and enthusiasts alike. In this course, you'll explore the foundations of AI, understand how it differs from regular computer programs, and learn the essential concepts behind generative models. Whether you’re curious about AI’s impact, want to enhance your professional skillset, or simply explore the latest trends, this course will equip you with the knowledge you need to thrive in today’s AI-driven world.

What You'll Learn:

  • What is Artificial Intelligence (AI)?Understand the core principles of AI and how it's revolutionizing industries.

  • How does AI differ from regular computer programs?Learn what makes AI unique and how it can solve complex problems.

  • Introduction to Generative AI:Explore the basics of Generative AI and how it creates new content like images, text, and more.

  • Real-World Examples of Generative AI:See how Generative AI is being used today in applications such as ChatGPT, DALL·E, and MidJourney.

  • How Does Generative AI Work in Simple Terms?Gain insights into how these powerful AI systems generate new and creative content from scratch.

  • The Rise of Generative AI:Discover why this technology has gained so much attention and its potential for future innovation.

  • Ethical Concerns in AI:Delve into the critical ethical questions surrounding AI, including bias, transparency, and responsible use.

  • AI Model Training and Lifecycle:Learn how AI models are trained, improved, and continuously developed to get smarter and more effective over time.

  • Machine Learning, Deep Learning, and Large Language Models (LLMs):Understand how these technologies fit into the broader AI ecosystem and power generative systems.

  • Natural Language Processing (NLP):Learn how AI "understands" human language and interacts seamlessly with people.

  • The Concept of Singularity:Explore the thought-provoking idea of AI surpassing human intelligence—what does it mean for the future?

  • Essential Skills for the Future of AI:Equip yourself with practical skills, from crafting better AI prompts to collaborating with AI to achieve your goals.

  • Writing Effective Prompts & AI Collaboration:Discover how to communicate effectively with AI and get the best possible results by crafting precise and creative prompts.

Who Is This Course For?

  • Anyone curious about Artificial Intelligence and its impact on the world

  • Professionals who want to integrate AI into their workflows or understand how to leverage it for business

  • Students and learners interested in expanding their knowledge in one of the most impactful technological trends

  • Creators and innovators who want to explore how AI can enhance creativity and production

Why This Course?

  • Beginner-Friendly: No prior AI knowledge required—this course explains complex topics in easy-to-understand language.

  • Comprehensive & Current: Covers everything from foundational AI concepts to the cutting-edge developments in Generative AI.

  • Real-World Examples: See how AI is being used in applications today and how you can apply it in your own work.

  • Future-Oriented: Understand the trends that will shape the future of AI and the skills you’ll need to stay ahead.

    Enroll Now:

Take your first step into the future of AI and transform how you think about technology. Whether you're looking to understand AI for personal interest or want to apply it professionally, this course will give you the skills and insights you need.

Thanks.

Steve Ballinger

Udemy Instructor Partner

FAQ

What is Artificial Intelligence (AI)? AI refers to the simulation of human intelligence by machines. This can include problem-solving, learning, reasoning, understanding language, and even visual perception. AI systems don’t “think” like humans but are designed to mimic human capabilities through data processing. For instance, when you use Google Maps for directions, it uses AI to analyze traffic data and recommend the best route.

How does AI differ from regular computer programs? Traditional programs follow a set of pre-written instructions to perform tasks, meaning they can’t adapt or change based on new data. AI, on the other hand, can learn from the information it's given and adapt its behavior. For example, a basic calculator performs the same function every time, while AI like Netflix’s recommendation engine changes based on what you’ve watched and what similar users enjoy.

What are some everyday examples of AI? AI is deeply integrated into our daily lives, often in ways we don’t notice. Some examples include:

  • Search engines like Google, which use AI to provide relevant results.

  • Spam filters in email accounts, which learn over time to detect unwanted messages.

  • Voice assistants like Siri or Alexa, which understand and respond to spoken commands.

  • Streaming platforms like Netflix or Spotify, which suggest movies or music based on past behavior.

What is Generative AI? Generative AI refers to algorithms that can create new content based on patterns they’ve learned from existing data. Unlike AI that only analyzes data, Generative AI can produce new text, images, music, and even code. For example, when you ask ChatGPT to write a poem, it’s generating new text based on its understanding of language from all the text it has been trained on.

How is Generative AI different from other types of AI? Most AI is designed for analysis or decision-making, like predicting whether an email is spam or not. Generative AI is different because it creates something new. For example, if you give it a sentence, it can continue the sentence, or if you describe a scene, it can generate an image. It’s more creative in nature, which is why it’s used for tasks like writing, designing, or composing music.

What does "generating" mean in the context of Generative AI? In Generative AI, "generating" means producing new content that wasn’t there before. The AI doesn’t just repeat or copy existing data—it uses what it’s learned to create original outputs. For example, if you ask a Generative AI to generate a painting of a sunset, it won’t pull an image from the internet but will create a new image based on its understanding of how sunsets typically look.

How does Generative AI work in simple terms? Generative AI works by learning patterns from large amounts of data. It doesn’t understand things the way humans do, but it can mimic human creativity by recognizing how pieces of data (words, pixels, sounds) are typically structured. It’s like learning how to write by reading many books—it doesn’t understand the meaning of the words but knows how they fit together.

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What's inside

Learning objectives

  • Understand the core concepts of artificial intelligence (ai) and how it differs from traditional computer programs.
  • Learn how generative ai works and explore real-world examples like chatgpt, image generators, and more.
  • Gain insights into the lifecycle of ai models, including how they are trained, improved, and continuously developed.
  • Master key ai technologies at an easy to understand level like machine learning, deep learning, and large language models (llms).
  • Explore the ethical considerations surrounding ai, including bias, transparency, and responsible use.
  • Develop practical skills for writing effective ai prompts and collaborating with ai tools for better results.
  • Prepare for the future by understanding how ai is transforming industries and the skills needed to stay competitive in an ai-driven world.
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Syllabus

Artificial Intelligence (AI) Fundamentals
What is Artificial Intelligence (AI)?
What is Generative AI & How is Generative AI different from other types of AI?
Read more
What are some common examples of Generative AI in use today? (Screencast)
Why has Generative AI become so popular now?
How does Generative AI work in simple terms
What are the different types of AI, and where does Generative AI fit in?
Singularity or will the machines take over?
What kind of data does Generative AI use?
Ethical and privacy concerns related to Artificial Intelligence (AI)
Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning
Tokens and use in AI & Natural Language Processing (NLP)
Artificial Intelligence (AI) Models
Artificial Intelligence (AI) Model lifecycle and how we interact with the model.
Prompt engineering tips to guide AI to give us the output we desire.
What does the future of Artificial Intelligence (AI) look like.
Top 4 Action Steps + Extra Step to take now.

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AI Fundamentals: Essential Guide to Artificial Intelligence with these activities:
Review Basic Programming Concepts
Reinforce your understanding of fundamental programming concepts to better grasp the logic behind AI algorithms.
Browse courses on Programming Fundamentals
Show steps
  • Review variables, data types, and control structures.
  • Practice writing simple programs in a language like Python.
  • Complete online coding exercises to test your knowledge.
Compile a List of AI Resources
Expand your knowledge of AI by compiling a list of useful resources, including websites, articles, and tools.
Show steps
  • Search for reputable AI websites and blogs.
  • Identify useful AI tools and libraries.
  • Organize the resources into categories.
  • Write a brief description of each resource.
Read 'Artificial Intelligence: A Modern Approach'
Gain a deeper understanding of AI principles and algorithms by studying a comprehensive AI textbook.
View Melania on Amazon
Show steps
  • Read the introductory chapters on AI and its history.
  • Focus on chapters related to machine learning and neural networks.
  • Take notes and summarize key concepts.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Build a Simple Chatbot
Apply your knowledge of AI and NLP by creating a basic chatbot that can respond to simple user queries.
Show steps
  • Choose a chatbot platform or library (e.g., Dialogflow, Rasa).
  • Define the chatbot's purpose and functionality.
  • Design the chatbot's dialogue flow and responses.
  • Implement and test the chatbot.
Create a Presentation on Generative AI
Solidify your understanding of Generative AI by creating a presentation explaining its concepts and applications.
Show steps
  • Research different types of Generative AI models.
  • Prepare slides explaining how Generative AI works.
  • Include real-world examples of Generative AI applications.
  • Practice your presentation and get feedback.
Read 'Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow'
Enhance your practical skills in machine learning by working through examples and exercises in a hands-on guide.
Show steps
  • Work through the examples in the book.
  • Experiment with different machine learning algorithms.
  • Apply the techniques to real-world datasets.
Contribute to an Open Source AI Project
Gain practical experience and contribute to the AI community by participating in an open-source project.
Show steps
  • Find an open-source AI project on GitHub or GitLab.
  • Review the project's documentation and contribution guidelines.
  • Identify a bug or feature to work on.
  • Submit a pull request with your changes.

Career center

Learners who complete AI Fundamentals: Essential Guide to Artificial Intelligence will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AI Fundamentals: Essential Guide to Artificial Intelligence.
Offers a practical approach to machine learning, deep learning, and neural networks using Python libraries like Scikit-Learn, Keras, and TensorFlow. It's ideal for learners who want to implement AI models and understand the underlying code. It complements the course by providing hands-on experience and practical examples. This book is valuable as a reference and for self-study.
This comprehensive textbook covering the entire field of AI, from its foundations to cutting-edge techniques. It provides a strong theoretical background for understanding AI concepts, including machine learning, deep learning, and natural language processing. While more in-depth than the course, it serves as an excellent reference for those seeking a deeper understanding. It is commonly used in university-level AI courses.

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