Skip to content
  1. Online
  2. Business
  3. Data analysis
Artificial Intellligence & Gen AI - Python Programming, Machine Learning & Data Analysis cover image

Artificial Intellligence & Gen AI - Python Programming, Machine Learning & Data Analysis
Learning Facility

Learn About AI & Machine Learning | 4 Course Bundle | 5 Free PDF Certificates | Tutor Support | Lifetime Access

Summary

Price
Save 4%
£21 inc VAT (was £21.99)
Offer ends 16 May 2026
Study method
Online, On Demand 
Duration
3.7 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Certificate of Completion - Free
  • Reed Courses Certificate of Completion - Free
1 student purchased this course

Add to basket or enquire

Overview

Artificial Intellligence & Gen AI - Python Programming, Machine Learning & Data Analysis

In the rapidly evolving landscape of modern technology, mastering Artificial Intellligence and AI has become a fundamental requirement for professionals seeking to lead in the digital age. This course is meticulously designed to provide a deep dive into Python as the primary language for building robust AI systems and implementing complex Machine Learning algorithms. By focusing on the intersection of Data analysis and Artificial Intellligence, students will learn how to transform raw information into actionable intelligence. The curriculum emphasizes the power of Python in streamlining the development of AI models, ensuring that every participant can navigate the intricacies of Machine Learning with confidence. As Data analysis becomes more integral to business strategy, the ability to leverage Artificial Intellligence and AI tools ensures that you remain at the forefront of technical innovation. Understanding how Machine Learning operates within an AI framework is essential for anyone looking to master Python for high-level Data analysis. Through this comprehensive exploration of Artificial Intellligence, you will see how AI is reshaping the world, driven by the versatility of Python and the predictive capabilities of Machine Learning. Ultimately, the synergy between Data analysis and Artificial Intellligence creates a powerful foundation for solving the most pressing challenges in the AI sector using advanced Python techniques and Machine Learning frameworks.

What you will learn from taking this course:

  • Gain proficiency in Python for developing advanced Artificial Intellligence and AI applications.

  • Master the core principles of Machine Learning to create predictive models.

  • Perform complex Data analysis to support Artificial Intellligence decision-making processes.

  • Understand the architecture of AI systems and how they integrate with Machine Learning.

  • Learn to utilize Python libraries specifically designed for Data analysis and Artificial Intellligence.

Key Features of the course:

  • Free PDF Certificate Included
  • Instant Access to the course materials
  • Lifetime Access

Certificates

Curriculum

6
sections
37
lectures
3h 44m
total

    • 1: Module 1 Introduction to Generative AI and Prompt Engineering. 08:00
    • 2: Module 2 Understanding Language Models. 08:00
    • 3: Module 3 Prompting Techniques and Best Practices. 07:00
    • 4: Module 4 Prompt Engineering for Text Generation. 08:00
    • 5: Module 5 Prompt Engineering for Visual and Multimodal Outputs. 08:00
    • 6: Module 6 Domain-Specific Prompting. 06:00
    • 7: Module 7 Advanced Prompting Techniques. 07:00
    • 8: Module 8 Evaluation and Optimisation. 06:00
    • 9: Module 9 Ethics, Bias, and Safety in Prompt Engineering. 07:00
    • 10: Module 10 Practical Applications and Capstone Projects. 06:00
    • 11: Assingment -

    • 12: Module 1 Getting Started with Python 06:00
    • 13: Module 2 Understanding Variables and Data Types 08:00
    • 14: Module 3 Mastering Conditional Statements 08:00
    • 15: Module 4 Exploring Loops and Iterations 08:00
    • 16: Module 5 Building and Using Functions 07:00
    • 17: Module 6 Working with Collection Data Structures 08:00

    • 18: Module 1 Introduction to Machine Learning 04:00
    • 19: Module 2 Linear Regression 04:00
    • 20: Module 3 Logistic Regression 04:00
    • 21: Module 4 Decision Trees and Random Forests 04:00
    • 22: Module 5 Support Vector Machines (SVMs) 04:00
    • 23: Module 6 k-Nearest Neighbors (k-NN) 05:00
    • 24: Module 8 Clustering 06:00
    • 25: Module 9 Dimensionality Reduction 11:00
    • 26: Module 10 Neural Networks 05:00

    • 27: Module 1 Introduction to Data Analysis 06:00
    • 28: Module 2 Statistical Fundamentals 06:00
    • 29: Module 3 Data Visualization 07:00
    • 30: Module 4 Exploratory Data Analysis (EDA) 06:00
    • 31: Module 5 Regression Analysis 06:00
    • 32: Module 6 Time Series Analysis 06:00
    • 33: Module 7 Machine Learning Basics 07:00
    • 34: Module 8 Data Mining Techniques 08:00
    • 35: Module 9 Big Data Analytics 07:00

    • 36: Review Request LF 01:00

    • 37: Claim Your Certificate 01:00

Description

The transition toward an AI-driven world necessitates a sophisticated understanding of Python and its role in modern Machine Learning applications. This course explores how Artificial Intellligence can be harnessed to perform advanced Data analysis, allowing for the creation of systems that learn and adapt over time. By utilizing Python, you will explore the various architectures of Machine Learning that power today’s most advanced AI solutions. We examine the critical role of Data analysis in refining Artificial Intellligence, ensuring that every AI model is built upon a foundation of accurate and insightful information. As you master Python, you will unlock new ways to implement Machine Learning across diverse industries, from healthcare to finance, where Data analysis and Artificial Intellligence are already making a significant impact. The course highlights how AI technologies rely on the efficiency of Python to process vast datasets, making Machine Learning more accessible and effective for large-scale Data analysis projects.

Furthermore, the integration of Generative AI within the broader field of Artificial Intellligence provides a unique perspective on how Python can be used to generate new content and insights. This syllabus covers the essential libraries in Python that facilitate Machine Learning and Data analysis, ensuring a smooth workflow for any AI project. By understanding the lifecycle of an Artificial Intellligence system, you will learn how AI and Machine Learning work together to automate complex Data analysis tasks. The course also addresses the ethical considerations of Artificial Intellligence, emphasizing the importance of responsible AI development when using Python and Machine Learning. With a strong focus on Data analysis, you will be prepared to contribute to the next generation of Artificial Intellligence and AI innovations. Through constant exposure to Python-based Machine Learning models, you will gain the expertise required to excel in the global AI market and lead Data analysis initiatives within your organization.

This is a self-paced learning platform, meaning you can study at your own pace and convenience. Additionally, each section of the course is divided in a way that allows you to easily pick up where you left off, making it easy to manage your time and progress throughout the course.

Who is this course for?

This course is ideal for individuals looking to build a career in Artificial Intellligence and AI by mastering the world's most popular language: Python. It is designed for aspiring data scientists who want to specialize in Machine Learning and Data analysis to drive technological change. Professionals in the IT sector who wish to update their skills with Artificial Intellligence knowledge will find the Python and Machine Learning modules highly beneficial. Whether you are a beginner interested in AI or a researcher looking to deepen your Data analysis capabilities, this course provides the necessary tools. Anyone motivated to understand the mechanics of Artificial Intellligence and the practical application of AI through Python, Machine Learning, and Data analysis should enroll.

Requirements

The Artificial Intellligence & Gen AI - Python Programming, Machine Learning & Data Analysis course no formal qualification to start

Career path

Completing this training opens various high-level opportunities in the AI industry, including:

  • Artificial Intellligence Engineer

  • Machine Learning Specialist

  • Data analysis Consultant

  • AI Solutions Architect

  • Python Developer for Artificial Intellligence

Topics of AI, Machine Learning, and Data analysis expertise ensures you are a top candidate for Artificial Intellligence roles globally.

Questions and answers

There are currently no Q&As for this course. Be the first to ask a question.

Ask a question

Reviews

Currently there are no reviews for this course. Be the first to leave a review.

Leave a review

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.
View all
Related searches: Business analysis courses, Analytics courses, Online courses

Interest free credit agreements provided by Zopa Bank Limited trading as DivideBuy are not regulated by the Financial Conduct Authority and do not fall under the jurisdiction of the Financial Ombudsman Service. Zopa Bank Limited trading as DivideBuy is authorised by the Prudential Regulation Authority and regulated by the Financial Conduct Authority and the Prudential Regulation Authority, and entered on the Financial Services Register (800542). Zopa Bank Limited (10627575) is incorporated in England & Wales and has its registered office at: 1st Floor, Cottons Centre, Tooley Street, London, SE1 2QG. VAT Number 281765280. DivideBuy's trading address is First Floor, Brunswick Court, Brunswick Street, Newcastle-under-Lyme, ST5 1HH. © Zopa Bank Limited 2026. All rights reserved.