Discover how to turn data into insight with Python. Learn to analyse, visualise, and build predictive models using modern tools like AutoML. Perfect for beginners ready to explore data science and machine learning.
Learning modes and locations may be different depending on the course start date. Please check the location of your chosen course and read our guide to learning modes and locations to help you choose the right course for you.
Start Date:08 Mar 2026
End Date:29 Mar 2026
Sun (Daytime):10:30 - 13:30
Choose either online or in-person
Location: Hybrid (choose either online or in-person)
Please note: We offer a wide variety of financial support to make courses affordable. Just visit our online Help Centre for more information on a range of topics including fees, online learning and FAQs.
This course explores the intersection between data analytics and machine learning, guiding you through the entire data science workflow—from problem understanding and data preparation to predictive modelling and result interpretation. Through practical, real-world scenarios and Python programming, you'll build both technical skills and the confidence to transform data into actionable insights relevant across various industries.
What will we cover?
The course covers each essential stage of the data science pipeline: data collection, preparation, exploratory data analysis (EDA), advanced visualization techniques, feature engineering, and statistical analysis. Participants will explore machine learning fundamentals, predictive modelling (including regression and classification), and ethical considerations in data use.
Key Python libraries such as pandas, NumPy, matplotlib, seaborn, scikit-learn, and modern AutoML tools like H2O will be utilized throughout.
What will I achieve? By the end of this course you should be able to...
Prepare and clean datasets effectively for analysis.
Conduct exploratory analyses and craft insightful visualizations.
Apply fundamental statistical methods and concepts.
Build and evaluate foundational machine learning models (e.g., linear regression, decision trees).
Utilize modern AutoML tools such as H2O for enhanced predictive modelling.
Communicate analytical findings clearly through data storytelling techniques.
Understand the impact and ethical implications of data science in decision-making.
What level is the course and do I need any particular skills?
This course is suitable for learners with basic familiarity with Python and data handling or those highly motivated to acquire these foundational skills quickly. Although beginner-friendly, prior programming experience and data manipulation knowledge will be advantageous. The initial sessions provide foundational programming and data analysis basics, ensuring all participants have a strong starting point. An enthusiasm for problem-solving and data-driven insights is essential.
How will I be taught, and will there be any work outside the class?
Teaching methods include concise lectures, live coding demonstrations, interactive discussions, and practical exercises using real-world datasets. Most learning activities occur during class; however, optional exercises and mini projects are available for those seeking further exploration and skill enhancement outside class hours.
Are there any other costs? Is there anything I need to bring?
There are no additional costs. All software used on the course is free to download and use and your tutor will recommend where to find this software. Unfortunately due to the range of hardware and software used by students at home, the College is unable to provide advice on installation issues.
When I've finished, what course can I do next?
City Lit offers a variety of progression courses in this subject area. Please click hereto view our courses.
Disclaimer: Use of Third-Party Software This course might require you to either use your own personal account or create an account for the purposes of this course. City Lit cannot accept any responsibility for any failings of the third party or provide technical support. Whilst using the software you will be responsible for abiding by the providers terms and conditions and maintaining your own work.
Thepan Ravindran is a Senior Generative AI engineer at KPMG UK. He holds an MSc in Big Data Science from Queen Mary University of London and completed the Applied Data Science Programme at the Massachusetts Institute of Technology (MIT). During his Master's, he served as a teaching demonstrator for Principles of Machine Learning. Originally from Malaysia and the first in his family to study abroad, he earned a full scholarship for his undergraduate degree before moving to London to further his academic and professional journey. At KPMG UK, Thepan designs and implements AI systems for global clients and trains non-technical professionals to confidently adopt AI. He has also contributed to data-driven projects with the World Health Organisation, Ministry of Health Malaysia and United Nations University. Thepan enjoys the creative problem-solving that programming offers and the impact it can create in society. He is passionate about teaching Python, machine learning, data science, financial modelling, and AI, and is known for helping learners who believe “coding isn’t for people like me” realise that they can do it too.
Please note: We reserve the right to change our tutors from those advertised. This happens rarely, but if it does, we are unable to refund fees due to this. Our tutors may have different teaching styles; however we guarantee a consistent quality of teaching in all our courses.
product
https://www.citylit.ac.uk/data-science-introduction1223401Data Science: introductionhttps://www.citylit.ac.uk/media/catalog/product/d/a/data-science-introduction-cppy49-1024.jpg259259GBPInStock/Courses/Courses/Business, marketing & technology/Courses/Business, marketing & technology/Web design and programming/Programming/Courses/Business, marketing & technology/Web design and programming/Courses/New courses228512111408168717431228512111687<p>Discover how to turn data into insight with Python. Learn to analyse, visualise, and build predictive models using modern tools like AutoML. Perfect for beginners ready to explore data science and machine learning.</p>002575546Data Science: introduction259259https://www.citylit.ac.uk/media/catalog/product/d/a/data-science-introduction-cppy49-1024_2.jpgInStockDaytimeSunHybrid (choose either online or in-person)Available courses1 to 4 weeksWeekend2026-03-08T00:00:00+00:00Beginners, Some experienceMar 2026Business, marketing & technologyCPPY50259259Data Science: introduction207168259Thepan Ravindrandata-science-introduction/cppy50-2526<p>Discover how to turn data into insight with Python. Learn to analyse, visualise, and build predictive models using modern tools like AutoML. Perfect for beginners ready to explore data science and machine learning.</p>0000-Available|2026-03-08 00:00:00<p>This course explores the intersection between data analytics and machine learning, guiding you through the entire data science workflow—from problem understanding and data preparation to predictive modelling and result interpretation. Through practical, real-world scenarios and Python programming, you'll build both technical skills and the confidence to transform data into actionable insights relevant across various industries.</p><p>Discover how to turn data into insight with Python. Learn to analyse, visualise, and build predictive models using modern tools like AutoML. Perfect for beginners ready to explore data science and machine learning.</p><p>The course covers each essential stage of the data science pipeline: data collection, preparation, exploratory data analysis (EDA), advanced visualization techniques, feature engineering, and statistical analysis. Participants will explore machine learning fundamentals, predictive modelling (including regression and classification), and ethical considerations in data use.</p><p>Key Python libraries such as pandas, NumPy, matplotlib, seaborn, scikit-learn, and modern AutoML tools like H2O will be utilized throughout.</p><ul><li>Prepare and clean datasets effectively for analysis.</li><li>Conduct exploratory analyses and craft insightful visualizations.</li><li>Apply fundamental statistical methods and concepts.</li><li>Build and evaluate foundational machine learning models (e.g., linear regression, decision trees).</li><li>Utilize modern AutoML tools such as H2O for enhanced predictive modelling.</li><li>Communicate analytical findings clearly through data storytelling techniques.</li><li>Understand the impact and ethical implications of data science in decision-making.</li></ul><p>This course is suitable for learners with basic familiarity with Python and data handling or those highly motivated to acquire these foundational skills quickly. Although beginner-friendly, prior programming experience and data manipulation knowledge will be advantageous. The initial sessions provide foundational programming and data analysis basics, ensuring all participants have a strong starting point. An enthusiasm for problem-solving and data-driven insights is essential.</p><p>Teaching methods include concise lectures, live coding demonstrations, interactive discussions, and practical exercises using real-world datasets. Most learning activities occur during class; however, optional exercises and mini projects are available for those seeking further exploration and skill enhancement outside class hours.</p><p>There are no additional costs. All software used on the course is free to download and use and your tutor will recommend where to find this software. Unfortunately due to the range of hardware and software used by students at home, the College is unable to provide advice on installation issues.</p><p>City Lit offers a variety of progression courses in this subject area. Please click <a href="https://www.citylit.ac.uk/media/wysiwyg/pdf/Web_Programming_Courses.pdf"><u>here</u> </a>to view our courses.</p><p>Disclaimer: Use of Third-Party Software<br/>This course might require you to either use your own personal account or create an account for the purposes of this course. City Lit cannot accept any responsibility for any failings of the third party or provide technical support. Whilst using the software you will be responsible for abiding by the providers terms and conditions and maintaining your own work.</p>Web design and programmingProgrammingvirtual207259168CPPY50NONESun08/03/26 - 29/03/2610:30 - 13:3010:3013:304 sessions (over 4 weeks)41 to 4 weeksDaytimeWeekendHybridHybrid (choose either online or in-person)Thepan RavindranBeginners, Some experienceAvailable courses2026-03-08T00:00:00+00:00Mar 2026Business, marketing & technology259259Data Science: introductiondata-science-introduction/cppy50-2526<p>Discover how to turn data into insight with Python. Learn to analyse, visualise, and build predictive models using modern tools like AutoML. Perfect for beginners ready to explore data science and machine learning.</p>0000-Available|2026-03-08 00:00:00<p>This course explores the intersection between data analytics and machine learning, guiding you through the entire data science workflow—from problem understanding and data preparation to predictive modelling and result interpretation. Through practical, real-world scenarios and Python programming, you'll build both technical skills and the confidence to transform data into actionable insights relevant across various industries.</p><p>Discover how to turn data into insight with Python. Learn to analyse, visualise, and build predictive models using modern tools like AutoML. Perfect for beginners ready to explore data science and machine learning.</p><p>The course covers each essential stage of the data science pipeline: data collection, preparation, exploratory data analysis (EDA), advanced visualization techniques, feature engineering, and statistical analysis. Participants will explore machine learning fundamentals, predictive modelling (including regression and classification), and ethical considerations in data use.</p><p>Key Python libraries such as pandas, NumPy, matplotlib, seaborn, scikit-learn, and modern AutoML tools like H2O will be utilized throughout.</p><ul><li>Prepare and clean datasets effectively for analysis.</li><li>Conduct exploratory analyses and craft insightful visualizations.</li><li>Apply fundamental statistical methods and concepts.</li><li>Build and evaluate foundational machine learning models (e.g., linear regression, decision trees).</li><li>Utilize modern AutoML tools such as H2O for enhanced predictive modelling.</li><li>Communicate analytical findings clearly through data storytelling techniques.</li><li>Understand the impact and ethical implications of data science in decision-making.</li></ul><p>This course is suitable for learners with basic familiarity with Python and data handling or those highly motivated to acquire these foundational skills quickly. Although beginner-friendly, prior programming experience and data manipulation knowledge will be advantageous. The initial sessions provide foundational programming and data analysis basics, ensuring all participants have a strong starting point. An enthusiasm for problem-solving and data-driven insights is essential.</p><p>Teaching methods include concise lectures, live coding demonstrations, interactive discussions, and practical exercises using real-world datasets. Most learning activities occur during class; however, optional exercises and mini projects are available for those seeking further exploration and skill enhancement outside class hours.</p><p>There are no additional costs. All software used on the course is free to download and use and your tutor will recommend where to find this software. Unfortunately due to the range of hardware and software used by students at home, the College is unable to provide advice on installation issues.</p><p>City Lit offers a variety of progression courses in this subject area. Please click <a href="https://www.citylit.ac.uk/media/wysiwyg/pdf/Web_Programming_Courses.pdf"><u>here</u> </a>to view our courses.</p><p>Disclaimer: Use of Third-Party Software<br/>This course might require you to either use your own personal account or create an account for the purposes of this course. City Lit cannot accept any responsibility for any failings of the third party or provide technical support. Whilst using the software you will be responsible for abiding by the providers terms and conditions and maintaining your own work.</p>Web design and programmingProgrammingconfigurable
14081687Programminghttps://www.citylit.ac.uk/courses/technology-science-and-business/web-design-and-programming/programming1/2/285/1211/1687/14081/Courses/Business, marketing & technology/Web design and programming/Programming
