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Allowing us to make sense of big data, Python is the future when it comes to data analytics.
The very popular Introduction to Data Analytics and Machine Learning with Python 3 short course has been designed to open the vast world of data analytics and machine learning to non-technical people without prior experience of the field, using the Python programming language.
Python 3 is the last iteration of the Python language, there will be no version 4 or 5. It will therefore be useful to learn the tools and techniques we teach in this course in Python 3.
As this is an introductory data analytics course you are not expected to have any data analytics or machine learning experience. The only requirements are successful completion of Introduction to programming with Python or knowledge of topics therein and knowledge of mathematical concepts such as those presented in the website (http://www.gcseguide.co.uk/mathsgcseguide.htm)
The Introduction to Data Analytics and Machine Learning with Python short course is taught over 10 weeks in the evenings, allowing you to continue with full-time employment. Studying one of our short courses is a fantastic way to learn new skills and can be used as a great way to further your career.
For students who already have a sound working knowledge of Python
You will learn the state of the art in data analytics and machine learning by leveraging the most widely used Python libraries, which are developed and maintained by big companies like Google, Facebook and Twitter.
As both data analytics and machine learning fields are vast and fast expanding, we will focus our efforts on grasping the foundations. The foundations which we will go through could enable you to get a junior position as a data analyst and/or machine learning engineer.
Libraries that will be taught in this course:
Applicants must have successfully completed the Introduction to programming with Python or have Python to a similar standard.
As this is an introductory data analytics course you are not expected to have any data analytics or machine learning experience.
Knowledge of mathematical concepts such as those presented in the website (http://www.gcseguide.co.uk/mathsgcseguide.htm) is essential.
Applicants must be proficient in written and spoken English.
Informal assessment through optional weekly assignments, which will build into a final project that will solve a real world problem using real world data, applying state of the art techniques taught during the course.