Course Overview
TOPPython for Data Science Primer is a two-day Python training course that introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it’s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice.
The course begins with quick overview of Python, with demonstrations of both script-based and web notebook-based Python, and then dives into the essentials of Python necessary to a data scientist. The tail end of the course explores a quick integration of these skills with key Data Science libraries including NumPy, Pandas and Matplotlib. This class is hands-on and includes light programming labs that introduce students to basic Python syntax and concepts applicable to using Python to work with data.
NOTE: Students heading into real project work right after training might consider a more robust hands-on course with deeper topics and lab coverage for similar subjects, such as the Introduction Python for Data Science
Scheduled Classes
TOP| 05/13/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led | (click to enroll)
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| 07/15/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led | (click to enroll)
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| 09/09/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led | (click to enroll)
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| 11/11/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led | (click to enroll)
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| 12/09/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led | (click to enroll)
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What You'll Learn
TOPThis 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.
Outline
TOPPlease 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.
- An Overview of Python
- Why Python?
- Python in the Shell
- Python in Web Notebooks (iPython, Jupyter, Zeppelin)
- Demo: Python, Notebooks, and Data Science
- Getting Started
- Using variables
- Builtin functions
- Strings
- Numbers
- Converting among types
- Writing to the screen
- Command line parameters
- Flow Control
- About flow control
- White space
- Conditional expressions
- Relational and Boolean operators
- While loops
- Alternate loop exits
- 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
- Working with files
- File overview
- Opening a text file
- Reading a text file
- Writing to a text file
- Reading and writing raw (binary) data
- Functions
- Defining functions
- Parameters
- Global and local scope
- Nested functions
- Returning values
- Essential Demos
- Sorting
- Exceptions
- Importing Modules
- Classes
- Regular Expressions
- The standard library
- Math functions
- The string module
- Dates and times
- Working with dates and times
- Translating timestamps
- Parsing dates from text
- Formatting dates
- Calendar data
- Python and Data Science
- Data Science Essentials
- Pandas Overview
- NumPy Overview
- SciKit Overview
- MatPlotLib Overview
- Working with Python in Data Science
Prerequisites
TOPTake 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)
- Excel Part 1 (helpful, but not required)
