TTPS4872: Python Primer for Data Science & Machine Learning / Hands-on Technical Overview

Become an EPIC Affiliate

To view the class schedule you need to become an Affiliate

  • Largest “Guaranteed To Run” public technical training schedules available
  • Easy to become an Affiliate – no charge or fee
Become an EPIC Affiliate

already an Affiliate?  Login

About this Course

Dive into the dynamic world of Python with our Quick Start to Python for Data Science Primer, tailored specifically for data analysts, business analysts, and technical managers keen on grasping the essentials of Python. This introductory course offers a friendly first step into the programming language that’s become a staple in data science. Through engaging instructor-led presentations and light hands-on activities, you’ll explore Python in various environments, including traditional scripts and interactive web notebooks like Jupyter. Discover how to execute simple scripts, manage data with fundamental Python structures, and apply basic programming concepts to real-world data scenarios.

By the end of this course, you’ll not only understand the core functionalities of Python but also appreciate how it can be leveraged in data science applications. You’ll be equipped to read and write basic files – a crucial skill for data management – and get introduced to powerful data science tools such as NumPy and Pandas for preliminary data analysis. Whether you’re preparing for more advanced training or looking to gain a quick, practical understanding of Python for your professional needs, this course promises a clear and concise introduction to the skills necessary to kickstart your journey in data science.

NOTE: This course is a great quick start to getting you conversant with and exposure to basic concepts. If you’re heading into project work or more advanced training soon after this course, you might consider the Fast Track to Python for Data Science (TTPS4873) as an alternative. That course offers additional topics and labs which provide more hands-on practice with core concepts and skills.

Audience Profile

This introductory-level course is geared for technical professionals new to Python. Roles include data analysts, developers, engineers or anyone tasked with utilizing Python for data analytics tasks. Familiarity with basic scripting skills is recommended, as this course does not teach general scripting basics.

At Course Completion

This hands-on course provides a solid starting point for business analysts, technical managers, or anyone interested in understanding the basics of Python in the context of data science. Attendees will be able to:

Run Python Scripts: You will be able to execute basic Python scripts using both traditional script-based environments and interactive web notebooks like Jupyter, which is fundamental for beginning any data science project.
Manipulate Simple Data Structures: Gain the ability to handle simple operations with Python's standard data structures (such as lists and dictionaries), enabling you to organize and manage data efficiently.
Apply Basic Python Commands for Data Analysis: Learn to use essential Python commands and functions for basic data analysis tasks, giving you a taste of what Python can offer in processing and analyzing data.
Read and Write Basic Files: Develop the skills to open, read, write, and close text files with Python, which is crucial for importing data for analysis and exporting results.
Get Acquainted with Python's Data Science Libraries: Acquire a foundational awareness of how libraries like NumPy and Pandas are used in Python for tasks like statistical analysis and data manipulation, preparing you for further exploration in the field of data science.

Outline

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We will work with you to tune this course and level of coverage to target the skills you need most. Course agenda, topics and labs are subject to adjust during live delivery in response to student skill level, interests and participation.

1. Getting Started: Explore the Python Environment

Python in the Shell
The python interpreter
Getting started with Jupyter notebook)
Python in Web Notebooks (iPython, Jupyter, Zeppelin)
Exploring Python, Notebooks, and Data Science

2. Variables and Values

Using variables
Builtin functions
Strings
Numbers
Converting among types

3. Basic Input and output

Writing to the screen
Command line parameters

4. Flow Control

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

5. Sequences, Arrays, Dictionaries and Sets

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

6. Working with files

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

7. Functions, modules, & packages

Defining functions
Parameters
Variable Scope
Creating modules
Using import
Creating packages

8. Python and Data Science

Python data science overview
NumPy Overview (with SciPy)
Pandas Overview
MatPlotLib Overview

Prerequisites

Familiarity with basic scripting skills is recommended, as this course does not teach general scripting basics.

TTPS4800 Introduction to Python Programming Basics