Introduction to Data Science short course
Our ethos
Our short courses are fun, social, and can help build future skills.
About the course
Introduction
Data science has evolved as one of the most promising and in-demand career paths for skilled professionals. Data professionals realise that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills.
The study of Data Science will enable you to analyse, communicate and re-evaluate raw data in order to make informed, valuable insights about that information, or to verify or challenge existing models, processes and theories.
Details
Date: For more information or to sign up to this course, please email employer@uwl.ac.uk.
Location: Online
Eligibility: This course is suitable for adults (18+).
Entry criteria
This is a beginners’ data science course. Ideally, students should have some exposure to Python programming, but this is not essential. However, students should be comfortable using a computer, including installing applications and saving and moving files.
Students will need their own computer (Windows or Mac) and have the required access rights to install the software. Students will be sent software install instructions in advance.
* Concession includes students (student ID required), and senior citizens 65+ (photo ID required)
* This course is suitable for adults (18+)
* The course will be Online (via Microsoft Teams) - the course link will be sent after purchase.
Course content
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Introduction to Data Science
We will take a brief look at what data science is and some typical data science applications.
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Being a Data Scientist
We will look at what data scientists do, the skills they need and the tools they use.
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The Machine Learning Process
We will work through a small example project using an “unplugged” paper-based approach, understanding the process for organising and executing a typical machine learning task. We will then repeat this task on a computer using Python.
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Building More Machine Learning Techniques
Building on the first exercise, we will learn new techniques such as classification, regression, and evaluating algorithms using the Python.
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Acquiring and Cleaning Data
We will look at where to collect data from and how to clean it and manipulate it into the right format to processing using Python.
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Data Visualisation
We will look at ways to present and visualise data and implement some code to visualise our data using the Python.
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Data Science Challenge
We will look at some typical data science questions and then work collaboratively to investigate and report back our answers.
Outcome and assessment
On successful completion of this course, you will be able to:
- Understand the typical tasks and activities of a data scientist.
- Load and manipulate data sets.
- Write Python code to analyse data.
- Write Python code to visualise data.
A number of activities and exercises will be set during each session to confirm and consolidate their understanding of each topic. A more comprehensive data investigation will cover about 2-3 hours of the course, where you must complete several iterations of a building machine learning model.
Lecturer
The University of West London invited Llewelyn to deliver the 'Introduction to Robotics', 'Introduction to the Internet of Things (IoT)' and 'Introduction to Artificial Intelligence and Machine Learning' courses due to his rich industrial background in practical applications of this innovative area.
Llewelyn Fernandes gained a degree in Computer Science from Brunel University. Working for a number of global IT Services Companies (such as Hitachi Consulting) specialising in business intelligence solutions, Llewelyn has established a highly successful career in software development and consultancy.
About professional short courses
Our series of high-quality short courses will enable you to build your learning in bite-sized chunks.
Our short courses are designed for individuals, as well as corporate and community groups. They are fun, social and provide opportunities to enhance your knowledge, improve your practical skills and tap into your potential.
If you would like us to deliver a short course that is not yet available, contact:
- Email - employer@uwl.ac.uk
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