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Practical Artificial Intelligence for Absolute Beginners
Xcel Learning

Complimentary Assessment | Digital Certificate | 24/7 Support | Lifetime Access | Transparent Pricing

Summary

Price
£30 inc VAT
Study method
Online, On Demand 
Course format
12 PDFs and 1 Assessment
Duration
1.4 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
Assessment details
  • Review Questions and Assessments (included in price)
Additional info
  • Tutor is available to students

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Overview

Practical Artificial Intelligence for Absolute Beginners course provides a clear and practical introduction to artificial intelligence for learners with little or no technical background. It begins by explaining core AI concepts in simple language, then gradually builds understanding through Python basics, data handling, and beginner-friendly machine learning ideas. Learners explore real-world applications such as natural language processing, computer vision, and modern generative AI tools, gaining both conceptual clarity and practical awareness. The course emphasizes hands-on thinking, ethical understanding, and real-life relevance rather than complex mathematics. By the end, learners will understand how AI works, where it is used, and how to begin applying it confidently in personal, academic, or professional contexts. This beginner-focused journey empowers anyone to move from curiosity to practical AI literacy and prepares them for deeper exploration in the evolving world of artificial intelligence.

Certificates

Assessment details

Review Questions and Assessments

Included in course price

Curriculum

This course contains

Format: 12 PDFs and 1 Assessment

Duration: 1h and 27m

Description

Exciting Journey Ahead: Discover What Awaits in This Course!

Chapter 1: Introduction to Artificial Intelligence

  1. What is Artificial Intelligence?
  2. History and Evolution of AI
  3. AI vs Machine Learning vs Deep Learning
  4. Real-World Applications of AI
  5. Common Myths and Misconceptions

Chapter 2: Understanding How AI Works

  1. Basic Concepts: Data, Algorithms, Models
  2. Supervised vs Unsupervised Learning
  3. Training vs Inference
  4. Role of Data in AI Systems
  5. AI Workflow Overview

Chapter 3: Setting Up Your AI Learning Environment

  1. Choosing Beginner-Friendly Tools
  2. Installing Python and Essential Tools
  3. Using Jupyter Notebooks
  4. Introduction to Google Colab
  5. Managing Files and Dependencies

Chapter 4: Python Basics for AI

  1. Python Syntax Essentials
  2. Variables, Data Types, and Operators
  3. Lists, Dictionaries, and Sets
  4. Functions and Modules
  5. Writing Clean and Readable Code

Chapter 5: Working with Data

  1. Types of Data in AI Projects
  2. Reading and Writing Data Files
  3. Data Cleaning Basics
  4. Data Visualization Fundamentals
  5. Introduction to Pandas and NumPy

Chapter 6: Introduction to Machine Learning

  1. What is Machine Learning?
  2. Types of Machine Learning Models
  3. Training a Simple Model
  4. Evaluating Model Performance
  5. Overfitting and Underfitting

Chapter 7: Practical Machine Learning Projects

  1. Predicting House Prices
  2. Spam Email Detection
  3. Customer Segmentation Basics
  4. Model Evaluation in Practice
  5. Improving Model Accuracy

Chapter 8: Introduction to Deep Learning

  1. What is Deep Learning?
  2. Neural Network Basics
  3. How Neural Networks Learn
  4. Popular Deep Learning Frameworks
  5. When to Use Deep Learning

Chapter 9: AI for Text and Language

  1. Natural Language Processing Basics
  2. Text Classification Projects
  3. Sentiment Analysis
  4. Chatbots and Conversational AI
  5. Using Pretrained Language Models

Chapter 10: AI for Images and Vision

  1. Introduction to Computer Vision
  2. Image Classification Basics
  3. Object Detection Overview
  4. Working with Image Datasets
  5. Real-World Vision Applications

Chapter 11: Using Modern AI Tools (No-Code & Low-Code)

  1. AI Tools for Non-Programmers
  2. Using Generative AI Assistants
  3. Automating Tasks with AI Tools
  4. Building AI Workflows Without Code
  5. Limitations of No-Code AI

Chapter 12: Responsible and Future AI

  1. Ethics and Bias in AI
  2. AI Safety and Risks
  3. Privacy and Data Responsibility
  4. Future Trends in AI
  5. Building Your AI Learning Roadmap

Don't miss out on the chance to discover your full potential. Enroll today and open the door to a world of opportunities. Receive an exclusive digital certificate upon completing the course!

Who is this course for?

This course is designed for complete beginners who want to understand artificial intelligence without prior technical experience. It suits students, professionals, and curious learners seeking practical skills to apply AI tools in everyday tasks, boost productivity, and build confidence in using modern intelligent technologies effectively across diverse real-world scenarios today.

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Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

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An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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