Python Primer

Python Primer, available at $19.99, has an average rating of 4.45, with 71 lectures, based on 12 reviews, and has 2210 subscribers.

You will learn about Learn the basics of python programming Begin using anaconda, jupyter notebooks and other python infrastructure Learn about how to use functions and classes for building modular programs Use matplotlib to create basic visualizations This course is ideal for individuals who are Absolute python programming beginners It is particularly useful for Absolute python programming beginners.

Enroll now: Python Primer

Summary

Title: Python Primer

Price: $19.99

Average Rating: 4.45

Number of Lectures: 71

Number of Published Lectures: 71

Number of Curriculum Items: 71

Number of Published Curriculum Objects: 71

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn the basics of python programming
Begin using anaconda, jupyter notebooks and other python infrastructure
Learn about how to use functions and classes for building modular programs
Use matplotlib to create basic visualizations

Who Should Attend

Absolute python programming beginners

Target Audiences

Absolute python programming beginners

This course is the first in a series of courses from FinanceAndPython. It works through the basics of python and how to write your first scripts. Upon completion you will be able to move on to some of the more advanced courses such as Basic Finance, Data Science, Investments, and more! The way that this course is taught is through a learning by doing model. You will be able to follow along as coding is done live in jupyter notebooks. Problem sets are also provided with solutions for each of the sections and a github repository with all of the course notebooks. To succeed in this course it is recommended to code along and begin experimenting with your own code.

The structure of the course is:

1. Variables: The basic building blocks of programming which hold information

2. If Statements & Boolean Values: Adding in ways to understand truth in statements and act on them

3. Lists, Sets and Tuples: Data structures for holding variables

4. Loops: Building intuition of how to iterate over sets of data

5. Functions: Creating repeatable patterns of code

6. Dictionaries: Branching out to a new data structure

7. Assertions and Docstrings: Building defensive and well explained code

8. Classes: Creating templates of objects

9. Matplotlib: Visualizing data

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Installing Anaconda

Lecture 3: Creating Your First Notebook

Chapter 2: Integers, Floats and Strings

Lecture 1: Variable Basics

Lecture 2: String Functionality

Lecture 3: String Indexing

Lecture 4: Floating Point Numbers

Lecture 5: Problem Set 1

Lecture 6: Problem Set 1 Solutions

Chapter 3: If Statements and Boolean Values

Lecture 1: Introduction

Lecture 2: If Statements

Lecture 3: Nesting If Statements

Lecture 4: Using Else and Elif

Lecture 5: Problem Set 2

Lecture 6: Problem Set 2 Solutions

Chapter 4: Lists, Sets, and Tuples

Lecture 1: Lists Introduction

Lecture 2: Using Append

Lecture 3: Using Extend

Lecture 4: Remove, Pop and Clear

Lecture 5: More Indexing Part 1

Lecture 6: More Indexing Part 2

Lecture 7: Count, Sort, Max & Min

Lecture 8: List Multiplication, List Comprehension, Modulo Function

Lecture 9: Zip Function, Nested Lists, Ranges

Lecture 10: Tuples

Lecture 11: Sets

Lecture 12: Problem Set 3

Lecture 13: Problem Set 3 Solutions

Chapter 5: Loops

Lecture 1: Loops Introduction

Lecture 2: Nested Loops, Break

Lecture 3: Continue, Using Lists

Lecture 4: Loop Examples

Lecture 5: While Loop

Lecture 6: Problem Set 4

Lecture 7: Problem Set 4 Solutions Part 1

Lecture 8: Problem Set 4 Solutions Part 2

Chapter 6: Functions

Lecture 1: Functions Introduction

Lecture 2: Arguments

Lecture 3: Returning Values

Lecture 4: Default Arguments

Lecture 5: Function Scope

Lecture 6: Mutable Structures

Lecture 7: Nested Functions

Lecture 8: Lambda Functions

Lecture 9: Problem Set 5

Lecture 10: Problem Set 5 Solutions

Chapter 7: Dictionaries

Lecture 1: Dictionaries Introduction

Lecture 2: Adding Keys

Lecture 3: Getting Keys/Values, Deleting Pairs

Lecture 4: Checking Keys

Lecture 5: Dictionary Example

Lecture 6: Loops and Dictionaries

Lecture 7: Problem Set 6

Lecture 8: Problem Set 6 Solutions

Chapter 8: Assertions and Docstrings

Lecture 1: Assertions

Lecture 2: Docstrings

Lecture 3: Problem Set 7

Lecture 4: Problem Set 7 Solutions

Chapter 9: Classes

Lecture 1: Classes Introduction

Lecture 2: Class Functions

Lecture 3: Class Attributes

Lecture 4: Class Initialization

Lecture 5: String Representations, Subclasses

Lecture 6: Problem Set 8

Lecture 7: Problem Set 8 Solutions Part 1

Lecture 8: Problem Set 8 Solutions Part 2

Chapter 10: Matplotlib and Graphing

Lecture 1: Introduction, Labels

Lecture 2: Legends, Axis Limits

Lecture 3: Color, Linestyle

Lecture 4: Problem Set 9

Lecture 5: Problem Set 9 Solutions

Instructors

Sean McOwen
Quantitative Analyst

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 1 votes
4 stars: 7 votes
5 stars: 4 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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