Introductory Python

Introductory Python
Course Overview

This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.

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Dates & Time Venue Tuition  
March 6, 2017 - March 29, 2017 7:00-9:30pm Workdays
Day 1: March 6, 2017
Day 2: March 8, 2017
Day 3: March 13, 2017
Day 4: March 15, 2017
Day 5: March 20, 2017
Day 6: March 22, 2017
Day 7: March 27, 2017
Day 8: March 29, 2017
New York
500 8th Ave., Suite 905
New York, NY 10018.0
$1590.00 Add to Cart
May 22, 2017 - June 19, 2017 7:00-9:30pm Workdays
Day 1: May 22, 2017
Day 2: May 24, 2017
Day 3: May 31, 2017
Day 4: June 5, 2017
Day 5: June 7, 2017
Day 6: June 12, 2017
Day 7: June 14, 2017
Day 8: June 19, 2017
New York
500 8th Ave., Suite 905
New York, NY 10018.0
$1590.00 Add to Cart
August 14, 2017 - September 11, 2017 7:00-9:30pm Workdays
Early-Bird Pricing!
Day 1: August 14, 2017
Day 2: August 16, 2017
Day 3: August 21, 2017
Day 4: August 23, 2017
Day 5: August 28, 2017
Day 6: August 30, 2017
Day 7: September 6, 2017
Day 8: September 11, 2017
New York
500 8th Ave., Suite 905
New York, NY 10018.0
$1590.00
$1510.50
Early-Bird Pricing!
Add to Cart
November 6, 2017 - December 4, 2017 7:00-9:30pm Workdays
Early-Bird Pricing!
Day 1: November 6, 2017
Day 2: November 8, 2017
Day 3: November 13, 2017
Day 4: November 15, 2017
Day 5: November 20, 2017
Day 6: November 27, 2017
Day 7: November 29, 2017
Day 8: December 4, 2017
New York
500 8th Ave., Suite 905
New York, NY 10018.0
$1590.00
$1510.50
Early-Bird Pricing!
Add to Cart
Questions? Read our FAQs & Refund Policy
For corporate training or small group training inquiry:
Instructors
Tony Schultz
Tony Schultz
Tony received his Ph.D. in Physics from the City University of New York and has taught at Sarah Lawrence College over the past decade. Tony specializes in developing machine learning and pattern recognition algorithms for processing motion capture data. He is passionate about teaching scientific computing and studying deep structures in human motion.
Zeyu Zhang
Zeyu Zhang
Zeyu obtained his master degree of Electrical Engineering from New York University. With a strong background in object oriented programming and a solid understanding of machine learning algorithms, he helps virtual and physical machines to evolve. Known for doing many difficult things well at the same time, or one simple thing very slowly, Zeyu thrives on problems that require multiple skills. Throw him into a pool of Python, C++, R, SQL, C#, HTML/CSS, JavaScript or find him actually swimming since retiring from his short-lived very-amateur basketball career.

Product Description



Details


Overview

This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.

Goals

This is a “short course” of four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class. Due to the focused nature of this course, there will be no individual class projects but the instructors will be available to help students who are applying Python to their own work outside of class.

Syllabus

Unit 1: List manipulation

  • Simple values and expressions
  • Defining functions, using ordinary syntax and lambda syntax
  • Lists
    • Built-in functions and subscripting
    • Nested lists
  • Functional operators: map and filter
  • List comprehensions
  • Multiple-list operations: map and zip
  • Functional operators: reduce

Unit 2: Strings and simple I/O

  • Characters
  • Strings as lists of characters
  • Built-in string operations
  • Input files as lists of strings
  • Print statement
  • Reading data from the web
    • Using the requests package
    • String-based web scraping (e.g. handling csv files)

Unit 3: Control structures

  • Statements vs. expressions
  • For loops
    • Variables in for loops
  • if statements
    • Simple and nested if statements
    • Conditional expressions in lambda functions
  • While loops
    • break and continue

Unit 4: Data Analysis Packages

  • NumPy
    • Ndarray
    • Subscripting and slicing
    • Operations
  • Pandas
    • Data Structure
    • Data Manipulation
    • Grouping and Aggregation

Preparation – How to set up Python environment

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