Python for Analytics
Taught by Dr. David Masad

Python for Analytics

taught by David Masad

 

 
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Aim of Course:

In this online course, "Python for Analytics," you'll learn everything you need to get you started using Python for data analysis.

We'll review basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.

About Python:  Python is a general-purpose programming language that's powerful, easy to learn and fast to code. It has a mature and growing ecosystem of open-source tools for mathematics and data analysis, and is rapidly becoming the language of choice for scientists and researchers of all stripes. Python code can be written like a traditional program, to execute an entire series of instructions at once; it can also be executed line by line or block by block, making it perfect for working with data interactively.  By the end of this course you should be able to

 

  • Construct conditional statements and loops
  • Work with strings, lists and dictionaries (in addition to variables)
  • Read and write data
  • Use Pandas for data anlysis
  • Group, aggregage, merge and join
  • Handle time series and data frames
  • Use matplotlib for visualization
  • Create format, and output figures

You will also be well positioned to move on to the Predictive Analytics series using Python.

 

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

WEEK 1:  Getting Started With Python

  • Using the Jupyter notebook
  • Python basics: variables, conditionals, loops
  • Data structures: lists and dictionaries


WEEK 2:  Data Handling and Strings

  • Reading data into memory
  • Working with strings
  • Catching exceptions to deal with bad data
  • Writing the data back out again


WEEK 3:  Python and Pandas

  • Using Pandas, the Python data analysis library
  • Series and Data Frames
  • Grouping, aggregating and applying
  • Merging and joining


WEEK 4:  Visualization

  • Visualization with matplotlib
  • Figures and subplots
  • Labeling and arranging figures
  • Outputting graphics

Homework:

The homework in this course consists of short answer questions to test concepts, guided exercises in writing code and guided data analysis problems using software.

This course also has example software codes, supplemental readings available online, and an end of course data analysis project.

Python for Analytics

Who Should Take This Course:
Data scientists, statisticians, software engineers who need to use Python for data analytics, including web scraping, pulling data, data cleaning, data prep and data analysis.
Level:
Introductory/Intermediate
Prerequisite:
You should have familiarity with programming, even if it is not Python.  If you are a newcomer to programming, you should take Python Programming Introduction first.
Organization of the Course:
Options for Credit and Recognition:
Course Text:

No text is required; all materials will be provided online.

If you want a reference, Python for Data Analysis is recommended. 

Software:
The required software is Python Programming Language.
Instructor(s):

Dates:

July 12, 2019 to August 09, 2019 November 15, 2019 to December 13, 2019 March 13, 2020 to April 10, 2020 July 10, 2020 to August 07, 2020 November 13, 2020 to December 11, 2020 March 12, 2021 to April 09, 2021

Python for Analytics

Instructor(s):

Dates:
July 12, 2019 to August 09, 2019 November 15, 2019 to December 13, 2019 March 13, 2020 to April 10, 2020 July 10, 2020 to August 07, 2020 November 13, 2020 to December 11, 2020 March 12, 2021 to April 09, 2021

Course Fee: $549

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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