Are you interested in using python for exploratory data analysis but have never programmed before?
Would you like to move away from spreadsheets and excel but don’t know how?
Would you like to create interesting data visualisations using programming tools but don’t know where to start?
If you’re interested in learning these skills then this course is aimed at you. This is a course for complete beginners and will teach you how to use python and its data science tools to analyse, plot and gain insight from data.
The course assumes absolutely no programming experience and starts by introducing you to python and teaching you all the python you need to know for data analysis.
It takes you step by step, teaching all the python necessary to work effectively with data.
You will learn how to:
•Install python using Anaconda
•Set up virtual environments in Anaconda
•Work with Jupyter Notebooks and how to really get the best from them
•Master the fundamentals of python
•Work with variables
•Work with data structures, such as lists and dictionaries
•Work with functions in python
•Import modules into a Jupyter Notebook
We cover the important data science modules in python. These are:
•Numpy
•Pandas
•Matplotlib
You will learn how to work with Numpy arrays and Pandas dataframes.
You will also learn how to problem solve and find help when you’re working on your own projects.
After introducing the essential fundamentals the course focus on projects. We cover the practical aspects of loading data into your notebook, exploring that data and visualizing it too.
you will look at and analyse Covid 19 data sets, you will plot case numbers and plot where the cases occurred on a map.
You will use matplotlib to plot share prices and you will use pandas to combine two datasets to find and visualize the location of the UK’s biggest energy consumers.
One of the projects will introduce you to the basics of SQLite and plotly.
By the time you finish working through this course you will have an excellent grasp of how to use python for data analysis.
