Deep Learning Neural Network with R Course

Description

Deep Learning Neural Network with R Course introduces learners to the structured logic behind neural networks using the R programming environment. The course focuses on how deep learning models are designed, structured, and evaluated, with clear explanations of key concepts such as neurons, layers, activation functions, and optimisation methods. Statistical foundations and algorithmic reasoning are presented in a clear, readable manner, making complex ideas approachable without oversimplifying the subject. Content is delivered entirely online, allowing learners to explore deep learning theory through guided explanations and code-based demonstrations in R.

This course also explores how neural networks are applied within data-driven decision-making, covering model performance, overfitting, and tuning techniques commonly used in deep learning workflows. Emphasis is placed on understanding how and why models behave as they do, supporting stronger analytical judgement and technical confidence. Designed for learners with an interest in data science, artificial intelligence, or advanced analytics, the course offers a structured learning path that adds clear value to professional development and strengthens knowledge in modern machine learning methods using R.

Learning Outcomes:

The Deep Learning Neural Network with R course is designed to provide learners with a comprehensive understanding of how to build and evaluate neural networks using R programming language. The course includes four modules that cover single-layer and multi-layer neural networks applied to agriculture and war datasets. Each module contains practical hands-on projects that allow learners to gain real-world experience in neural network development and evaluation. By the end of the course, learners will have a solid understanding of neural network concepts, R programming language, and practical experience with real-world datasets.

⊱⊱Deep Learning Neural Network with R Course Curriculum

How is the course assessed?

Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%.

Exam & Retakes:
It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.

Certification
Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).

CPD

10 CPD hours / points Accredited by CPD Quality Standards

Who is this course for?

Requirements

There are no formal entry requirements for the course, with enrollment open to anyone!

Career path

Entry-level positions such as Data Analysts can expect to earn between £25,000 to £35,000 per annum, whereas senior-level positions such as Machine Learning Engineers can earn upwards of £70,000 per annum.

Certificates

Certificate of completion

Digital certificate - £9

You can apply for a CPD Accredited PDF Certificate at the cost of £9.

Certificate of completion

Hard copy certificate - £15

Hard copy can be sent to you via post at the expense of £15.