As Artificial Intelligence (AI) becomes more common in daily life, this Level 3 qualification aims to give you the key skills for AI programming using Python, which is a great first language to learn if you’re new to AI.
In our Level 3 AI Programming with Python course , you’ll learn basic Python functions, how to write scripts, and explore important Python libraries. You’ll also cover version control with GitHub and get an introduction to Deep Learning (making predictions from data), including key math concepts like linear algebra and calculus.
It provides an alternative route to careers in coding and programming, while fostering practical and hands-on learning to prepare you for a future career in this sector.
The course is delivered in a virtual classroom, so you will need access to a laptop/computer with an internet connection to complete the course.
On completion of the course, you’ll receive an industry-recognised Level 3 qualification in AI Programming with Python.
As part of the course, you’ll complete the following key units:
This unit introduces you to coding in Python. You will develop various programs to deepen your understanding of data types, operators, control flow, functions, and script writing in Python. Additionally, you will gain insights into object-oriented programming.
This unit will provide you with an understanding of libraries used in Python programming and the software needed to support their use. You will learn about Anaconda, Jupyter Notebook, and the use of libraries including NumPy, Pandas, Matplotlib and Seaborn.
On completion of this unit, you will understand version control, be able to create GitHub Repository, use commits for version control, be able to work with remotes effectively, be able to tag, branch and merge version control using GitHub, review a repositories history and undo changes and understand the importance for staying in sync with remote repository for version control.
You will be introduced to deep learning and the critical role of gradient descent in optimising models. You will learn how to use deep learning techniques with PyTorch and how to train neural networks effectively. This unit also covers the application of vectors, linear combinations, and algebra in deep learning. Additionally, you will gain an understanding of linear transformations and matrices with NumPy, as well as the role of calculus in deep learning, particularly how derivatives are integral to the learning process.
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