Python Primer for Data Science and Machine Learning | Hands-on Technical Overview (TTPS4872)

Course Objectives

This course is approximately 40% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises.  Our engaging instructors and mentors are highly experienced practitioners who bring years of current "on-the-job" experience into every classroom.  Throughout the hands-on course students will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques.

Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level):

• How to work with Python interactively in web notebooks
• The essentials of Python scripting
• Key concepts necessary to enter the world of Data Science via Python

Need different skills or topics?  If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate.  We offer additional python, data science, AI / machine learning and other related topics that may be blended with this course for a track that best suits your needs. Our team will collaborate with you to understand your needs and will target the course to focus on your specific learning objectives and goals.

Course Prerequisites

This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course.

Take Before: Students should have skills at least equivalent to the following course(s) or should have attended as a pre-requisite:

• Understanding Data Science | A Technical Overview – 1 day (helpful but not required)
• Working with Excel (helpful, but not required)

Please see the Related Courses tab for specific Pre-Requisite courses, Related Courses that offer similar skills or topics, and next-step Learning Path recommendations.

Course Agenda

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most.

1. An Overview of Python

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

2. Getting Started

• Using variables
• Builtin functions
• Strings
• Numbers
• Converting among types
• Writing to the screen
• Command line parameters

3. Flow Control

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

4. 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

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

6. Functions

• Defining functions
• Parameters 
• Global and local scope
• Nested functions
• Returning values

7. Essential Demos

• Sorting
• Exceptions
• Importing Modules
• Classes
• Regular Expressions

8. The standard library

• Math functions
• The string module

9. Dates and times

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

10. Python and Data Science

• Data Science Essentials
• Pandas Overview
• NumPy Overview
• SciKit Overview
• MatPlotLib Overview
• Working with Python in Data Science

Course Materials

Student Materials: Each student will receive a Student Guide with course notes, code samples, software tutorials, diagrams and related reference materials and links (as applicable). Our courses also include step by step hands-on lab instructions and and solutions, clearly illustrated for users to complete hands-on work in class, and to revisit to review or refresh skills at any time. Students will also receive related (as applicable) project files, code files, data sets and solutions required for the hands-on work.

Classroom Setup Made Simple:  Our dedicated tech team will work with you to ensure your classroom and lab environment is setup, tested and ready to go well in advance of the course delivery date, ensuring a smooth start to class and seamless hands-on experience for your students. We offer several flexible student machine setup options including guided manual set up for simple installation directly on student machines, or cloud based / remote hosted lab solutions where students can log in to a complete separate lab environment minus any installations, or we can supply complete turn-key, pre-loaded equipment to bring ready-to-go student machines to your facility.  Please inquire for details, options and pricing.