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Hands-on Python primer for data scientists

Course Code: 1197

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$1495

|

Hands-on Python primer for data scientists

Learn Python essentials for business and data analysis in a data science environment

Course Code : 1197

$1495

Overview
Schedule classes
What you'll learn
Outline
Prerequisites
Who should attend

Overview

This two day course introduces data analysts and business analysts, or anyone interested in data science to the Python programming language. The course aims to provide a baseline understanding of core concepts that can serve as a knowledge base to follow up with more in-depth training and real-world practice.

Schedule Classes

Looking for more sessions of this class?

Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 5 days

Live Virtual Classroom
Duration: 5 days

What You'll learn

Overview of Python
Demonstration of script-based and web notebook-based Python
Essentials of Python for a data scientist
Key data science libraries, such as NumPy, Pandas, Matplotlib
Essentials of Python scripting

Outline

Module 1: An overview of Python

Why Python?
Python in the Shell
Python in the Web Notebooks (iPython, Jupyter, Zeppelin)
Demo: Python, Notebooks, Data Science

Module 2: Getting started

Using variables
Built-in functions
Strings
Numbers
Converting among types
Writing to the screen
Command-line parameters

Module 3: Flow control

About flow control
White space
Conditional expressions
Relational and Boolean operators
While loops
Alternate loop exits

Module 4: Sequences, arrays, dictionaries and sets

About sequences
Lists and list methods
Tuples
Indexing and slicing
Iterating through a sequence
Sequence functions, keywords, operators
List comprehensions
Generator expressions
Nested sequences
Working with dictionaries
Working with sets

Module 5: Working with files

File overview
Opening a text file
Reading a text file
Writing to a text file
Reading and writing raw (binary) data

Module 6: Functions

Defining functions
Parameters
Global and local scope
Nested functions
Returning values

Module 7: Essential demos

Sorting
Exceptions
Importing modules
Classes
Regular expressions

Module 8: The standard library

Math functions
The string module

Module 9: Dates and times

Working with dates and times
Translating timestamps
Parsing dates from text
Formatting dates
Calendar data

Module 10: Python and data science

Data science essentials
Pandas overview
NumPy overview
SciKit overview
MatPlotLib overview
Working with Python in data science

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Prerequisites

Participants need to have a basic understanding of data science and a working knowledge of Microsoft Excel.

Who Should Attend

The course is highly recommended for –

Data analysts
Business analysts
Anyone else interested in data science

Interested in this course? Let’s connect!

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