Machine Learning (Bronze)




DofE – Skills Section – Machine Learning (Bronze)

Participating in the Skills Section of the Duke of Edinburgh (DofE) Bronze Award through Computer Science or coding is an excellent choice, providing an opportunity to develop valuable technical skills and knowledge.

Here are some Machine Learning activities that you could consider:

Option 1 – Introduction to Machine Learning

Introductory course on machine learning fundamentals.

Learn basic concepts such as supervised learning, unsupervised learning, and reinforcement learning, as well as common machine learning algorithms.

Option 2 – Data Exploration and Visualisation

Learn how to explore and visualise data using tools like Python’s pandas and Matplotlib libraries.

Gain hands-on experience in loading, cleaning, and analysing datasets, as well as creating visualisations to understand data patterns.

Option 3 – Building a Linear Regression Model

Build their first machine learning model by implementing a simple linear regression algorithm.

Learn how to train the model on a dataset, evaluate its performance, and make predictions based on input data.

Option 4 – Classification with Logistic Regression

Expand their machine-learning skills by implementing a logistic regression classifier.

Learn how to classify data into different categories based on input features and evaluate the model’s accuracy and performance.

Option 5 – Exploring Clustering Algorithms

Experiment with clustering algorithms such as k-means clustering or hierarchical clustering.

Learn how to group data points into clusters based on similarity and visualise the clustering results to gain insights into the underlying data structure.

Option 6 – Introduction to Neural Networks

Learn basics of neural networks and deep learning.

Learn about neural network architecture, activation functions, and training algorithms, and implement a simple neural network using libraries like TensorFlow or PyTorch.

Option 7 – Image Classification with Convolutional Neural Networks (CNNs)

Learn how to build a convolutional neural network (CNN) for image classification tasks.

Understand the architecture of CNNs, preprocess image data, train the model on a dataset like MNIST or CIFAR-10, and evaluate its performance.

Option 8 – Natural Language Processing (NLP) Basics

Participants can explore the field of natural language processing (NLP) by working on text classification or sentiment analysis tasks.

They will learn how to preprocess text data, extract features, and train machine-learning models to analyse and understand human language.

These options provide participants with a structured pathway to learn the fundamentals of machine learning

Gain practical experience with different algorithms and techniques

Build a solid foundation for further exploration in this exciting field as part of the Bronze level of the DofE Skills Section.

Before you join this course

Our online classroom software necessitates a minimum upload speed of 5 Mbps and a minimum download speed of 15 Mbps.

The majority of broadband providers offer packages that surpass these requirements.

Before you commit to this course, please check your broadband speed by clicking the link shared below.

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