Learning Python on Google Cloud

Learning Python on Google Cloud, available at $34.99, has an average rating of 4.4, with 51 lectures, based on 22 reviews, and has 336 subscribers.

You will learn about Fundamentals of Python Python on Google Cloud Variables and String Methods using Python How to use Python Lists How to use Python Sets and Dictionaries Conditional Statements and Loops in Python Intro and usage of Python Modules How to use List Comprehension Function Creation in Python Introduction to Numpy Using Numpy Methods Introduction to Pandas Descriptive Stats in Pandas (describe method) Sorting your Pandas DataFrame Filtering your Pandas DataFrame Exporting Pandas Result to Google Drive Connecting to Postgres and Redshift Databases Querying Postgres and Redshift Databases Reading Data with Pandas (.csv and databases) Aggregation Using Pandas New Fields in Pandas Joins and Merging Data using Pandas Using Functions with Pandas (apply method) Charting with Pandas Foundations for being a Data Scientist Skills for being a next level Data Analyst This course is ideal for individuals who are Analysts or Business Professionals or Data Enthusiasts or Beginning Python Developers or Data Analysts or Data Scientists It is particularly useful for Analysts or Business Professionals or Data Enthusiasts or Beginning Python Developers or Data Analysts or Data Scientists.

Enroll now: Learning Python on Google Cloud

Summary

Title: Learning Python on Google Cloud

Price: $34.99

Average Rating: 4.4

Number of Lectures: 51

Number of Published Lectures: 51

Number of Curriculum Items: 51

Number of Published Curriculum Objects: 51

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Fundamentals of Python
Python on Google Cloud
Variables and String Methods using Python
How to use Python Lists
How to use Python Sets and Dictionaries
Conditional Statements and Loops in Python
Intro and usage of Python Modules
How to use List Comprehension
Function Creation in Python
Introduction to Numpy
Using Numpy Methods
Introduction to Pandas
Descriptive Stats in Pandas (describe method)
Sorting your Pandas DataFrame
Filtering your Pandas DataFrame
Exporting Pandas Result to Google Drive
Connecting to Postgres and Redshift Databases
Querying Postgres and Redshift Databases
Reading Data with Pandas (.csv and databases)
Aggregation Using Pandas
New Fields in Pandas
Joins and Merging Data using Pandas
Using Functions with Pandas (apply method)
Charting with Pandas
Foundations for being a Data Scientist
Skills for being a next level Data Analyst

Who Should Attend

Analysts
Business Professionals
Data Enthusiasts
Beginning Python Developers
Data Analysts
Data Scientists

Target Audiences

Analysts
Business Professionals
Data Enthusiasts
Beginning Python Developers
Data Analysts
Data Scientists

What sets this course apart from all others is how quickly we dive into the material and the selective topics covered to get you comfortable with Python in less than a day! That’s right, this course is basically a crash course designed for learners that want to get up and running with Python as quick as possible and begin applying their Python skills.

This course requires 0 installation of any kind. All you’ll need is

your web browser and
a Gmail account,

In Lesson 01, we selectively cover

data and variable types,
methods,
conditional statements and
loops

In Lesson 02, we go over

modules (a.k.a. libraries)
string methods
list comprehension
custom functions

In Lesson 03, using the foundation above, we pick up on data analysis tools and techniques such as

Numpy
Pandas
Reading Files and Querying Databases
Pandas Methods for Stats and Aggregation
Other Pandas Built in Functions and Features, including charts / visualizations

From the core to the advanced tools that you want to have to get your skills and career to the next level!

Course Curriculum

Chapter 1: Lesson 01

Lecture 1: Introduction

Lecture 2: Welcome to Google Colaboratory

Lecture 3: Exploring the Google Colab Notebook

Lecture 4: Introducing Strings and Numbers

Lecture 5: Variables

Lecture 6: String Concatenation

Lecture 7: Practice Exercise 01

Lecture 8: Solution to Exercise 01

Lecture 9: Introduction to Python Lists

Lecture 10: List Methods

Lecture 11: Practice Exercise 02

Lecture 12: Solution to Exercise 02

Lecture 13: Sets

Lecture 14: Dictionaries

Lecture 15: Exercise 03

Lecture 16: Solution to Exercise 03

Lecture 17: Conditional Statements

Lecture 18: For Loops

Lecture 19: Exercise 04

Lecture 20: Solution to Exercise 04

Chapter 2: Lesson 02

Lecture 1: Python Modules (a.k.a. Libraries)

Lecture 2: Python Modules Continued

Lecture 3: String Methods

Lecture 4: Exercise 05

Lecture 5: Solution to Exercise 05

Lecture 6: List Comprehension

Lecture 7: Intro to Functions

Lecture 8: More on Functions

Lecture 9: Exercise 06

Lecture 10: Solution to Exercise 06

Lecture 11: The Ninth Inning

Chapter 3: Lesson 03

Lecture 1: Intro to Numpy

Lecture 2: Numpy Continued

Lecture 3: Intro to Pandas

Lecture 4: Pandas Describe

Lecture 5: Exercise 07

Lecture 6: Solution to Exercise 07

Lecture 7: Pandas Sort

Lecture 8: Pandas Filter

Lecture 9: Exporting to the Cloud!

Lecture 10: Connecting to Redshift & Postgres

Lecture 11: Reading Database Queries

Lecture 12: Aggregating Data with Pandas

Lecture 13: Column Naming

Lecture 14: Joins with Pandas

Lecture 15: Removing Duplicate Fields

Lecture 16: Applying Functions in Pandas

Lecture 17: Exercise 08

Lecture 18: Solution to Exercise 08

Lecture 19: Pandas Charts

Lecture 20: Final Thoughts and Your Continued Growth

Instructors

Oscar Valles
Analytics and Business Intelligence Professional

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 3 votes
4 stars: 10 votes
5 stars: 9 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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