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30-Day Money-Back Guarantee

This course includes:

  • 18 hours on-demand video
  • 32 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
IT & Software Other IT & Software Python

Python for ALL, Data Science Worked Examples

Test Studies in Data Science
Rating: 4.6 out of 54.6 (10 ratings)
98 students
Created by Matthew Fried
Published 10/2018
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Run faster than a speeding bullet and leap over tall buildings in a single bound - in the Pythonic way!

Requirements

  • None

Description

This course covers the basics of Python with many, many practice examples. The focus is learning the language with many exercises. The only way to learn is engagement and this course provides the full experience. The goal, from there, is to see various applications, particularly in finance.   We cover a plethora of important concepts and implementations in Python. The user will learn to be fully competent and capable of using Python to apply to a work environment.  We also have several worked examples with Data Science applications, wherein the student learns the ins-and-outs of real world practices.

Who this course is for:

  • Everyone

Course content

22 sections • 105 lectures • 18h 13m total length

  • Preview14:30
  • Github
    07:00
  • Markdown
    05:22
  • Which environment to choose?
    16:24

  • Gathering Information
    06:52
  • Integrating Colab/Jupyter with Python
    07:26

  • Preview03:08
  • Preview03:58
  • Input and Conversion
    02:50
  • Rounding and Built-In Functions
    05:10
  • Practice Problem: Finding the Present Value
    02:26

  • String Concatenation and the Print Function Explored
    03:36
  • f-strings and .format
    06:39

  • Python Exercises
    08:36

  • Control Statements 1
    06:34
  • Control Statements 2
    05:45
  • Control Statements 3
    10:48
  • Review of Control Statements
    06:22
  • Practice with Control Statements
    04:30

  • While Loops
    10:46
  • For Loops
    05:25
  • Review and Practice 1
    19:06
  • Review and Practice 2
    07:08
  • Finding Primes
    04:11
  • Checking for Coprimes
    02:19
  • Pythagorean Triples
    05:00
  • Practice Questions for Review
    19:02

  • Big Overview of Lists
    29:19
  • Lists
    02:59
  • Random Numbers and Filling in Lists
    07:15
  • Creating and Traversing a 2d List
    06:58
  • More on creating a 2d list
    02:02
  • List functions
    06:10
  • List Comprehension Examples
    07:47
  • Zip and DeepCopy
    04:26
  • Tuples
    01:26
  • Basic I/O
    02:52
  • Financial Examples
    11:48

  • Functions 1
    05:41
  • Functions 2
    17:38
  • Euler Totient Function Concept
    07:20
  • Euler Totient Function Code
    04:02
  • Collatz Conjecture Concept
    03:14
  • Collatz Conjecture Code
    04:05
  • Statistics with Functions (Avg and Std)
    05:17
  • Functions with Lists
    04:04
  • Function Review Problems
    16:39

  • Concepts in Strings
    08:04

Instructor

Matthew Fried
Prof.
Matthew Fried
  • 4.4 Instructor Rating
  • 676 Reviews
  • 2,010 Students
  • 11 Courses

Matthew Fried teaches full time.  He is an educational professional who has many years experience in guiding students to reach their full potential. He has taught computers, networking, math, and finance for nearly a decade.  He has taught graduate and undergraduate courses in each subject. He has developed student-centric platforms and feels very strongly that every student can accomplish their goals.

He is full time in Lander College and a Lecturer in SUNY Farmingdale. He teaches courses in programming and derivatives in Queens College and University of Connecticut.  He regularly teaches C++, C#, Python, Networking, Financial Modelling and more.

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