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No-Code AI & Machine Learning for Beginners
Xcel Learning

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Summary

Price
£22 inc VAT
Study method
Online, On Demand 
Duration
1.2 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

No-Code AI & Machine Learning for Beginners is a practical, step-by-step course designed to help non technical learners understand and apply Artificial Intelligence without writing code. This course introduces core AI concepts, data fundamentals, supervised and unsupervised learning, model evaluation, computer vision, natural language processing, and real-world deployment using intuitive no-code platforms. Learners will gain hands-on experience preparing data, building predictive models, interpreting performance metrics, and integrating AI solutions into business workflows. Emphasis is placed on practical application, ethical responsibility, and strategic thinking rather than programming complexity. By the end of the course, participants will be able to design end-to-end AI projects, create a professional portfolio, and confidently use no-code tools to solve real-world problems across industries.

Certificates

Assessment details

Review Questions and Assessments

Included in course price

Curriculum

13
sections
13
lectures
1h 11m
total

Description

Discover the Exciting Subjects Awaited in This Course!

Chapter 1: Introduction to AI & Machine Learning

  1. What is Artificial Intelligence?
  2. What is Machine Learning?
  3. AI vs ML vs Deep Learning
  4. Real-World Applications of AI
  5. The Rise of No-Code AI Platforms

Chapter 2: Understanding Data Fundamentals

  1. Types of Data (Structured vs Unstructured)
  2. Features and Labels Explained
  3. Data Collection Methods
  4. Data Cleaning Basics
  5. Introduction to Data Ethics & Privacy

Chapter 3: No-Code AI Tools Landscape

  1. Overview of Popular No-Code AI Platforms
  2. Comparing Features and Use Cases
  3. Cloud-Based vs Local No-Code Tools
  4. Choosing the Right Tool for Your Project
  5. Setting Up Your First No-Code AI Account

Chapter 4: Data Preparation Without Coding

  1. Importing Data from Spreadsheets
  2. Data Cleaning Using Visual Interfaces
  3. Handling Missing Values
  4. Data Transformation & Formatting
  5. Splitting Data (Training vs Testing)

Chapter 5: Building Your First ML Model

  1. What is a Machine Learning Model?
  2. Selecting Target Variables
  3. Training a Model Using No-Code Tools
  4. Understanding Model Parameters
  5. Saving and Exporting Models

Chapter 6: Supervised Learning Made Simple

  1. Introduction to Supervised Learning
  2. Classification Problems Explained
  3. Regression Problems Explained
  4. Training Classification Models (No-Code)
  5. Training Regression Models (No-Code)

Chapter 7: Unsupervised Learning for Beginners

  1. What is Unsupervised Learning?
  2. Clustering Concepts
  3. Customer Segmentation Example
  4. Anomaly Detection Basics
  5. Visualizing Clusters Without Code

Chapter 8: Model Evaluation & Improvement

  1. Accuracy, Precision, Recall Simplified
  2. Confusion Matrix Explained
  3. Avoiding Overfitting
  4. Cross-Validation Basics
  5. Improving Model Performance Without Coding

Chapter 9: AI for Computer Vision (No-Code)

  1. Introduction to Computer Vision
  2. Image Classification Projects
  3. Object Detection Basics
  4. Using Drag-and-Drop Vision Tools
  5. Deploying a Vision Model

Chapter 10: AI for Natural Language Processing (No-Code)

  1. Introduction to NLP
  2. Text Classification Projects
  3. Sentiment Analysis
  4. Chatbots Without Coding
  5. Deploying NLP Models

Chapter 11: Deploying & Integrating AI Solutions

  1. What is Model Deployment?
  2. Embedding AI into Websites
  3. Automating Workflows with AI
  4. Monitoring Model Performance
  5. Maintaining and Updating Models

Chapter 12: Capstone Projects & Future Learning

  1. End-to-End No-Code AI Project
  2. Business Use Case Implementation
  3. Ethical AI in Practice
  4. Building Your AI Portfolio
  5. Next Steps in AI & Machine Learning

Unleash Your Potential: Join Us Today and Elevate Your Skills with a Prestigious Digital Certificate upon Course Completion!

Who is this course for?

This course is designed for beginners, students, entrepreneurs, and professionals with little to no programming experience who want to explore AI and machine learning. It is ideal for those seeking to build practical solutions using no-code tools, automate tasks, and understand core concepts without diving into complex coding or technical backgrounds.

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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.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

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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