AI for Beginners

AI for Beginners is a Breni path that explains artificial intelligence in plain English, with no coding or maths required. In 7 courses it covers how machines learn from data, how large language models such as chatbots produce text, how to get reliable results from AI tools, and the risks of bias, privacy loss and made-up answers. Learners finish able to explain how AI works and use it at work. The ethics course follows the hands-on ones, and courses open in sequence as each is completed.

• 7 courses
• 10 learning objectives
• Level: beginner
• Language: English
• Price: Subscription, free trial

What you will be able to do

• Explain the difference between AI, machine learning and deep learning in plain terms
• Describe how a large language model predicts text and why it sometimes invents facts
• Write prompts with context, examples and a clear format to get better AI answers
• Check an AI answer for errors, bias and missing sources before relying on it
• Plan how to use an AI tool in a real work or study task

Full curriculum

Part 1 · What AI is

1. AI in Plain English: Everyday Concepts

Define artificial intelligence and recognise where it already shows up in daily life. Units, in order: What counts as artificial intelligence; Narrow AI and general AI; Key moments in the history of AI; AI in phones, search, maps and shopping; Common myths about AI.

• — What is Artificial Intelligence
  Learn how machines mimic human thinking and what counts as AI.
  • Defining Artificial Intelligence
  • Smart versus Simple Machines
• — Narrow AI and General AI
  Explore systems built for single tasks versus human-level intelligence.
  • Understanding Narrow AI
  • What is General AI
• — Key Moments in AI History
  Trace the major breakthroughs that shaped modern artificial intelligence.
  • Early Ideas and Turing Test
  • Modern AI Growth
• — AI in Everyday Life
  Find out where AI hides in your phone and apps.
  • Phones and Search Engines
  • Maps and Shopping Apps
• — Common Myths About AI
  Separate science fiction from facts regarding artificial intelligence.
  • Consciousness and Feelings
  • Job Loss and Control

2. How Machines Learn

Explain how a model learns patterns from data and then uses them on new examples. Units, in order: Data, patterns and predictions; Training a model compared with using one; Learning from labelled and unlabelled data; Neural networks drawn as simple pictures; Why more and better data matters.

3. How Large Language Models Work

Describe how chatbots turn a prompt into an answer, and where that process goes wrong. Units, in order: Tokens: how text is broken up; Predicting the next token; Pre-training and fine-tuning; The context window; Why models make things up.

Part 2 · Using AI

4. Getting Good Results from AI Tools

Write prompts that get accurate, useful answers and check what comes back. Units, in order: Clear instructions and a stated goal; Giving context and examples; Asking for a specific format; Checking answers against sources; Using AI for writing, research and study.

5. Images, Voice and Vision AI

Explain how AI creates images, understands speech and recognises what is in a picture. Units, in order: How image generators work; Speech recognition and synthetic voices; Computer vision; Models that handle text, images and sound together; Spotting deepfakes.

Part 3 · AI in the world

6. AI Risks and Ethics

Weigh the main risks of AI and the questions people are still debating. Units, in order: Bias in training data; Privacy and personal data; Copyright and AI-generated work; Misinformation at scale; Safety and alignment in plain terms.

7. AI at Work

Choose where AI can help in a real job and judge whether it did. Units, in order: Finding tasks AI does well; Choosing a tool for the job; AI agents that take actions; Measuring whether AI saved time; Workplace rules for using AI.

Sample: AI in Plain English: Everyday Concepts

The opening tier, (What is Artificial Intelligence). Learn how machines mimic human thinking and what counts as AI.

Defining Artificial Intelligence

Understand how computers solve tasks like humans do.

Smart versus Simple Machines

Spot the difference between basic tools and smart systems.

Questions about AI for Beginners

Can I learn artificial intelligence without coding?

Yes. AI for Beginners on Breni explains how AI works and how to use it without any code. If you want to build models yourself, the Machine Learning for Beginners path is the next step.

What is the difference between AI and machine learning?

Artificial intelligence is the broad goal of making computers do tasks that need human-like judgement. Machine learning is one way to reach it, where a model learns patterns from data instead of following hand-written rules.

Is this AI course good for complete beginners?

Yes. The first course starts with what counts as AI and where you already use it, with no technical background assumed.

Does the path teach prompt writing?

Yes, the fourth course covers prompts, context, examples and checking answers. The Prompt Engineering path on Breni goes much further.

Do I get a certificate for this AI path?

Yes. Finishing all 7 courses earns a Breni certificate of completion. It is a record of finishing the path, not a degree.

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