Data Science 2: Machine Learning
In this course, we continue our journey in the world of data science, moving from the data wrangling and Python explanations covered in the previous course to an overview of the most popular machine learning models in the industry. We start with linear regression and progress to the latest advancements with gradient boosting, as well as clustering and feature selection/ranking algorithms. Each topic provides a theoretical understanding paired with a hands-on exercise to be solved in Python using real-world data.
£270.00
Starts 9th September 2026
Data Science 2: Machine Learning
In this course, we continue our journey in the world of data science, moving from the data wrangling and Python explanations covered in the previous course to an overview of the most popular machine learning models in the industry. We start with linear regression and progress to the latest advancements with gradient boosting, as well as clustering and feature selection/ranking algorithms. Each topic provides a theoretical understanding paired with a hands-on exercise to be solved in Python using real-world data.
£270.00
Starts 9th September 2026
About This Course
- 14 Modules
- 16 Hours
- Level: Intermediate
- Language: English
- Course Type: Self-paced
- CPD Accredited Certificate
- Online Learning
Who Is This Course For
This course is designed for anyone with a basic understanding of data science concepts. The only prerequisite is a solid understanding of the Python programming language. The knowledge gained in this course can serve as the first step toward a deeper dive into any of the related concepts. This certification will be advantageous for anyone seeking an entry-level data science job or looking to advance their education in the fields of data science, machine learning, and/or artificial intelligence.
What you'll learn
- Fundamental machine learning concepts.
- An understanding of various performance metrics for different models and techniques to optimise them.
- How to work with supervised versus unsupervised data.
- How to deal with overfitting and underfitting.
- How to manipulate data and build classical machine learning models.
- Bagging and Boosting techniques.
- Dimensionality reduction.
Course Content
Meet Your Instructor
Dr. Sterling Ramroach
Sterling has a Ph.D. in Machine Learning from The University of the West Indies. He moved to London after his Ph.D. to pursue a Computer Vision Researcher position in the industry. His Ph.D. research focused on accelerating machine learning techniques with parallel processing and applying it to bioinformatics. His work is published in peer-reviewed scientific journals including Molecular Omics, Expert Systems with Application, and BMJ Innovations.
Our Partners
We are proud to partner with the leading In2scienceUK as a step towards achieving our mission of imparting quality education and knowledge across the globe.
How This Course Supports Your Career Development
Biotechnology is one of the fastest-evolving industries in the world, creating demand for professionals with knowledge of emerging fields such as genomics, gene therapy, bioinformatics, artificial intelligence and precision medicine.
Our learners include students, graduates, researchers and professionals from leading universities, pharmaceutical companies, biotechnology organisations and research institutions across the UK and internationally.
Upon successful completion, learners receive a CPD-accredited certificate and earn recognised CPD hours that can be included on CVs, LinkedIn profiles, professional portfolios and CPD records.
By completing this course, you will strengthen your scientific knowledge, earn valuable CPD hours and demonstrate a commitment to continuous professional development within the life sciences sector.
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Usually, there are no general prerequisites when enrolling for any individual courses on cbehx.co.uk. However, some courses are certainly more advanced than others that are of introductory and intermediate level. For advanced-level courses, prior knowledge on the topic will be helpful for understanding complex concepts but not mandatory.
The relevant information about the suggested knowledge and background that might be helpful to follow each course is provided on the respective course registration page.
Yes, the courses are flexible and self-paced to suit your schedule. The term “self-paced” implies that the courses do not follow a pre-assigned schedule for learning within the course duration. You will be able to access all the course materials for each course that you have enrolled in as soon as the course begins.
The course completion certificate is CPD accredited. For more informations please visit https://cpduk.co.uk
