Python Primer for Data Scientists: A Technical Overview (TTPS4871)
Python Primer for Data Scientists: A Technical Overview (TTPS4871) Course Details:
Python Primer for Data Scientists – A Technical Overview is a one-day 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, SciKit, and Matplotlib.
Call (919) 283-1653 to get a class scheduled online or in your area!
Session 1: An Overview of Python
- Why Python?
- Python in the Shell
- Python in Web Notebooks (iPython, Jupyter, Zeppelin)
- Demo: Python, Notebooks, and Data Science
Session 2: Getting Started
- Using variables
- Builtin functions
- Strings
- Numbers
- Converting among types
- Writing to the screen
- Command line parameters
Session 3: Flow Control
- About flow control
- White space
- Conditional expressions
- Relational and Boolean operators
- While loops
- Alternate loop exits
Session 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
Session 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
Session 6: Functions
- Defining functions
- Parameters
- Global and local scope
- Nested functions
- Returning values
Session 7: Essential Demos
- Sorting
- Exceptions
- Importing Modules
- Classes
- Regular Expressions
Session 8: The standard library
- Math functions
- The string module
Session 9: Dates and times
- Working with dates and times
- Translating timestamps
- Parsing dates from text
- Formatting dates
- Calendar data
Session 10: Python and Data Science
- Data Science Essentials
- Pandas Overview
- NumPy Overview
- SciKit Overview
- MatPlotLib Overview
- Working with Python in Data Science
*Please Note: Course Outline is subject to change without notice. Exact course outline will be provided at time of registration.
Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, demo, hands-on lab exercises, and lab review. This course is “skills-centric”, designed to train attendees in core Python data science skills at an introductory level, coupling the most current, effective techniques with best practices.
Working within in an engaging, hands-on learning environment, guided by our expert, students will explore:
- 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
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.