SUPERVISED MACHINE LEARNING

In this course you will code along with me and learn:

- how decision trees work and what type of machine learning they fit into

- advantages and disadvantages of decision trees

- good types of data to use with decision trees

- how to train a decision tree in scikitlearn

- practice training a decision tree on a real data set

When you have watched the videos you can practice your new skills with the workbooks.

This course contains 17 video tutorials with over 53 minutes of videos and 1 downloadable and printable workbook.  On average it takes around 3.5 hours to fully complete. When you buy a course you get an email with the link and password to the course. All you need to do is go to the relevant web page and type in the password. You will then have unlimited access to the course for one month.

This course is suitable for people who have Python programming skills including understanding how to use and manipulate numerical data, strings, Booleans, lists, tuples and ranges.  You should be comfortable with the programming fundamentals of if, elif and else statements, for and while loops and functions.  Be able to plot scatter, line, histograms and pie charts in Matplotlib, and how to choose which graph to use.  You should have good working knowledge of NumPy arrays, array management and manipulation.  Be able to read in data using Pandas, complete basic data manipulation and export data.  You should be comfortable doing data manipulation in Pandas, creating one data frame from different data sets and how to do basic data cleaning.  No prior experience with machine learning is required.

To get the full benefit from this course you will need to be comfortable with the following skills: 

- complete the Set Up Python course https://swamphen.co.uk/set-up-python   

- have a good foundation in Python programming 

- how to define and manipulate numerical data types, strings and Booleans

- how to set up, slice, order, add, append and alter mutable sequences lists, lists of lists, immutable sequences tuples and ranges

- how to write and use functions with Python data, loops and control flow

- how to choose the correct graph to use and produce bespoke graphs of different types, including line, scatter, histogram, pie chart

- NumPy array management and alterations including different dimensional arrays and how to use with control flow

- read data into Pandas and know how to describe this data

- perform statistics on your Pandas data

- select rows, columns, ranges and sort or filter your Pandas data

- how to export data from Pandas

- be able to do row and column manipulation in Pandas and create one data frame from different data

- know the basics of data cleaning and how to deal with missing data and NaN's

You can get these skills from Swamphen Enterprise's previous courses at www.swamphen.co.uk/python-series-information and www.swamphen.co.uk/graph-plotting-series-information and www.swamphen.co.uk/data-science-series-information.  Our courses follow a structured learning progression to help you on your journey.  

When you have booked onto the course you will receive a document by email. Download this document to get the url and password for the course.

WHERE NEXT?

Congratulations on getting to the end of the current Python and Data Science courses. Check back soon to see if more content has been added, or look at some of the other course savailable at www.swamphen.co.uk/online-learning