Unlock your data science potential with our CPD Certified and Industry Standard “Data Science & Machine Learning with R Training.” Master R programming, data manipulation, visualization, and machine learning fundamentals—plus career-building modules like freelancing and personal branding. Enrol now to elevate your career with globally recognised skills in high demand!
4.6
(2 Reviews)
22 Students
Exclusive Deal! 94% Off, Today Only!
Sale Ends In
The demand for data science professionals in the UK is growing rapidly, with a 37% increase in job vacancies over the past year alone. As companies increasingly rely on data-driven decisions, mastering data science and machine learning skills has never been more crucial. This nationally recognised course equips you to meet this urgent industry need with confidence.
Through practical modules covering R programming, data manipulation, visualisation, and machine learning, you will gain hands-on experience essential for real-world applications. From understanding data structures to building web apps with R Shiny, every section is designed to enhance your technical expertise and analytical thinking, preparing you for immediate success in the field.
By completing this CPD Accredited course, you’ll boost your employability, open doors to promotion, and tap into a thriving sector hungry for skilled professionals. Whether aiming for a new role or career growth, this training offers the tools and credentials to help you stand out and advance in data science.
By completing this course, learners will be able to:Â Â
This course is ideal for:Â Â
After completing the MCQ assessment, you will qualify for the CPD Certificate from HF Online as proof of your continued professional development. You can order your certificate at a cost of £10 for PDF and £29 for hardcopy certificate or both for £39.
For assessing your learning, you have to complete an automated MCQ exam. It is required for the students to score at least 60% to pass the exam. Learners can apply for the certificate after they clear the exam.
There are assignment questions provided at the end of the course. You are suggested to complete the questions to enrich your understanding of the course. You can complete this according to your preferred time. The expert tutor will provide feedback on your performance after assessing your assignment.
Completing this diploma can lead to the following UK job roles:Â Â
| Data Science and Machine Learning Course Intro | |||
| What is Data Science | 00:10:00 | ||
| Machine Learning Overview | 00:05:00 | ||
| Who is This Course for | 00:03:00 | ||
| Data Science and Machine Learning Marketplace | 00:05:00 | ||
| Data Science and Machine Learning Job Opportunities | 00:03:00 | ||
| Getting Started with R | |||
| Getting Started | 00:11:00 | ||
| Basics | 00:06:00 | ||
| Files | 00:11:00 | ||
| RStudio | 00:07:00 | ||
| Tidyverse | 00:05:00 | ||
| Resources | 00:04:00 | ||
| Data Types and Structures in R | |||
| Unit Introduction | 00:30:00 | ||
| Basic Type | 00:09:00 | ||
| Vector Part One | 00:20:00 | ||
| Vectors Part Two | 00:25:00 | ||
| Vectors – Missing Values | 00:16:00 | ||
| Vectors – Coercion | 00:14:00 | ||
| Vectors – Naming | 00:10:00 | ||
| Vectors – Misc | 00:06:00 | ||
| Creating Matrics | 00:31:00 | ||
| List | 00:32:00 | ||
| Introduction to Data Frames | 00:19:00 | ||
| Creating Data Frames | 00:20:00 | ||
| Data Frames: Helper Functions | 00:31:00 | ||
| Data Frames Tibbles | 00:39:00 | ||
| Intermediate R | |||
| Intermediate Introduction | 00:47:00 | ||
| Relational Operations | 00:11:00 | ||
| Conditional Statements | 00:11:00 | ||
| Loops | 00:08:00 | ||
| Functions | 00:14:00 | ||
| Packages | 00:11:00 | ||
| Factors | 00:28:00 | ||
| Dates and Times | 00:30:00 | ||
| Functional Programming | 00:37:00 | ||
| Data Import or Export | 00:22:00 | ||
| Database | 00:27:00 | ||
| Data Manipulation in R | |||
| Data Manipulation in R Introduction | 00:36:00 | ||
| Tidy Data | 00:11:00 | ||
| The Pipe Operator | 00:15:00 | ||
| The Filter Verb | 00:22:00 | ||
| The Select Verb | 00:46:00 | ||
| The Mutate Verb | 00:32:00 | ||
| The Arrange Verb | 00:10:00 | ||
| The Summarize Verb | 00:23:00 | ||
| Data Pivoting | 00:42:00 | ||
| JSON Parsing | 00:11:00 | ||
| String Manipulation | 00:33:00 | ||
| Web Scraping | 00:59:00 | ||
| Data Visualization in R | |||
| Data Visualization in R Section Intro | 00:17:00 | ||
| Getting Started | 00:16:00 | ||
| Aesthetics Mappings | 00:25:00 | ||
| Single Variable Plots | 00:37:00 | ||
| Two Variable Plots | 00:21:00 | ||
| Facets, Layering, and Coordinate Systems | 00:18:00 | ||
| Styling and Saving | 00:12:00 | ||
| Creating Reports with R Markdown | |||
| Creating with R Markdown | 00:29:00 | ||
| Building Webapps with R Shiny | |||
| Introduction to R Shiny | 00:26:00 | ||
| A Basic R Shiny App | 00:31:00 | ||
| Other Examples with R Shiny | 00:34:00 | ||
| Introduction to Machine Learning | |||
| Machine Learning Part 1 | 00:22:00 | ||
| Machine Learning Part 2 | 00:47:00 | ||
| Starting A Career in Data Science | |||
| Starting a Data Science Career Section Overview | 00:03:00 | ||
| Data Science Resume | 00:04:00 | ||
| Getting Started with Freelancing | 00:05:00 | ||
| Top Freelance Websites | 00:05:00 | ||
| Personal Branding | 00:05:00 | ||
| Importance of Website and Blo | 00:04:00 | ||
| Networking Do’s and Don’ts | 00:04:00 | ||
| Resources | |||
| Resources – Data Science & Machine Learning with R | 00:00:00 | ||
| Assignment | |||
| Assignment – Data Science & Machine Learning with R Training | 00:00:00 | ||
| Data Science and Machine Learning Course Intro | |||
| What is Data Science | 00:10:00 | ||
| Machine Learning Overview | 00:05:00 | ||
| Who is This Course for | 00:03:00 | ||
| Data Science and Machine Learning Marketplace | 00:05:00 | ||
| Data Science and Machine Learning Job Opportunities | 00:03:00 | ||
| Getting Started with R | |||
| Getting Started | 00:11:00 | ||
| Basics | 00:06:00 | ||
| Files | 00:11:00 | ||
| RStudio | 00:07:00 | ||
| Tidyverse | 00:05:00 | ||
| Resources | 00:04:00 | ||
| Data Types and Structures in R | |||
| Unit Introduction | 00:30:00 | ||
| Basic Type | 00:09:00 | ||
| Vector Part One | 00:20:00 | ||
| Vectors Part Two | 00:25:00 | ||
| Vectors – Missing Values | 00:16:00 | ||
| Vectors – Coercion | 00:14:00 | ||
| Vectors – Naming | 00:10:00 | ||
| Vectors – Misc | 00:06:00 | ||
| Creating Matrics | 00:31:00 | ||
| List | 00:32:00 | ||
| Introduction to Data Frames | 00:19:00 | ||
| Creating Data Frames | 00:20:00 | ||
| Data Frames: Helper Functions | 00:31:00 | ||
| Data Frames Tibbles | 00:39:00 | ||
| Intermediate R | |||
| Intermediate Introduction | 00:47:00 | ||
| Relational Operations | 00:11:00 | ||
| Conditional Statements | 00:11:00 | ||
| Loops | 00:08:00 | ||
| Functions | 00:14:00 | ||
| Packages | 00:11:00 | ||
| Factors | 00:28:00 | ||
| Dates and Times | 00:30:00 | ||
| Functional Programming | 00:37:00 | ||
| Data Import or Export | 00:22:00 | ||
| Database | 00:27:00 | ||
| Data Manipulation in R | |||
| Data Manipulation in R Introduction | 00:36:00 | ||
| Tidy Data | 00:11:00 | ||
| The Pipe Operator | 00:15:00 | ||
| The Filter Verb | 00:22:00 | ||
| The Select Verb | 00:46:00 | ||
| The Mutate Verb | 00:32:00 | ||
| The Arrange Verb | 00:10:00 | ||
| The Summarize Verb | 00:23:00 | ||
| Data Pivoting | 00:42:00 | ||
| JSON Parsing | 00:11:00 | ||
| String Manipulation | 00:33:00 | ||
| Web Scraping | 00:59:00 | ||
| Data Visualization in R | |||
| Data Visualization in R Section Intro | 00:17:00 | ||
| Getting Started | 00:16:00 | ||
| Aesthetics Mappings | 00:25:00 | ||
| Single Variable Plots | 00:37:00 | ||
| Two Variable Plots | 00:21:00 | ||
| Facets, Layering, and Coordinate Systems | 00:18:00 | ||
| Styling and Saving | 00:12:00 | ||
| Creating Reports with R Markdown | |||
| Creating with R Markdown | 00:29:00 | ||
| Building Webapps with R Shiny | |||
| Introduction to R Shiny | 00:26:00 | ||
| A Basic R Shiny App | 00:31:00 | ||
| Other Examples with R Shiny | 00:34:00 | ||
| Introduction to Machine Learning | |||
| Machine Learning Part 1 | 00:22:00 | ||
| Machine Learning Part 2 | 00:47:00 | ||
| Starting A Career in Data Science | |||
| Starting a Data Science Career Section Overview | 00:03:00 | ||
| Data Science Resume | 00:04:00 | ||
| Getting Started with Freelancing | 00:05:00 | ||
| Top Freelance Websites | 00:05:00 | ||
| Personal Branding | 00:05:00 | ||
| Importance of Website and Blo | 00:04:00 | ||
| Networking Do’s and Don’ts | 00:04:00 | ||
| Resources | |||
| Resources – Data Science & Machine Learning with R | 00:00:00 | ||
| Assignment | |||
| Assignment – Data Science & Machine Learning with R Training | 00:00:00 | ||

