Data Wrangling in Pandas for Machine Learning Engineers

Data Wrangling in Pandas for Machine Learning Engineers, available at $44.99, has an average rating of 4.25, with 89 lectures, 7 quizzes, based on 118 reviews, and has 806 subscribers.

You will learn about Youll learn data wrangling in Python. Youll be prepared for interview questions on data wrangling in Python. Data wrangling is what machine learning engineers do around 70% of the time and the skills in this course will put you ahead of others in the real world. Youll be adept using the most important Python library for data wrangling. This course is ideal for individuals who are If youre interested in becoming a machine learning engineer then this course is for you. or If youre interested in becoming a data engineer then this course is for you. or If youre a professional in any discipline that needs to become adept at data wrangling then this course is for you. It is particularly useful for If youre interested in becoming a machine learning engineer then this course is for you. or If youre interested in becoming a data engineer then this course is for you. or If youre a professional in any discipline that needs to become adept at data wrangling then this course is for you.

Enroll now: Data Wrangling in Pandas for Machine Learning Engineers

Summary

Title: Data Wrangling in Pandas for Machine Learning Engineers

Price: $44.99

Average Rating: 4.25

Number of Lectures: 89

Number of Quizzes: 7

Number of Published Lectures: 89

Number of Published Quizzes: 7

Number of Curriculum Items: 96

Number of Published Curriculum Objects: 96

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Youll learn data wrangling in Python.

Youll be prepared for interview questions on data wrangling in Python.

Data wrangling is what machine learning engineers do around 70% of the time and the skills in this course will put you ahead of others in the real world.

Youll be adept using the most important Python library for data wrangling.

Who Should Attend

If youre interested in becoming a machine learning engineer then this course is for you.

If youre interested in becoming a data engineer then this course is for you.

If youre a professional in any discipline that needs to become adept at data wrangling then this course is for you.

Target Audiences

If youre interested in becoming a machine learning engineer then this course is for you.

If youre interested in becoming a data engineer then this course is for you.

If youre a professional in any discipline that needs to become adept at data wrangling then this course is for you.

Reviews: 

The examples given and explanation provided by the instructor were great. He is entertaining as well as knowledgeable about the subject. – Prakash Shelke

Spectacular step by step instructions with great examples and labs. -Donato

Great course !!!!! You learn how to use the Pandas library for its own sake and not as a part of some courses devoted to other topics. -Giovanni De Angelis

The course is really impressive. Tons of information, and I learned a great deal. I had no Python background, and now I feel a lot more confident about working with Python than ever. Thanks for the course.  Austin

Honestly Mike your classes speak for themselves. They’re informative, concise and just really well put together. They’re exactly the kind of courses I look for. –Alex El

I have been a software engineer for more years than I care to admit. I found the presentation, speed and depth fit what I was looking for perfectly. I believe at this point I understand enough about Pandas so that I can move forward with this branch of learning. – Danny

Course Description 

Welcome to Data Wrangling in Pandas for Machine Learning Engineers

This is the second course in a series designed to prepare you for becoming a machine learning engineer.

I’ll keep this updated and list only the courses that are live.  Here is a list of the courses that can be taken right now.  Please take them in order. The knowledge builds from course to course. 

The Complete Python Course for Machine Learning Engineers 

Data Wrangling in Pandas for Machine Learning Engineers (This one) 

Data Visualization in Python for Machine Learning Engineers

Learn the single most important skill for the machine learning engineer: Data Wrangling

A complete understanding of data wrangling vernacular.

Pandas from A-Z. 

The ability to completely cleanse a tabular data set in Pandas. 

Lab integrated. Please don’t just watch. Learning is an interactive event.  Go over every lab in detail. 

Real world Interviews Questions.

The knowledge buildsfrom course to course in a serial nature. Withoutthe first course many students might struggle with this one. Thank you. 

Many new to machine learning believe machine learning engineers spend their days building deep
neural models in Keras or SciKit-Learn. I hate to be the bearer of bad news but that isn’t the case.

A recent study from Kaggle determined that 80% of time data scientists and machine learning engineers
spend their time cleaning data. The term used for cleaning data in data science circles is called data wrangling.  

In this course we are going to learn Pandasusing a lab integrated approach. Programming is something you have to do in
order to master it. You can’t read about Python and expect to learn it. 

Pandas is the single most important library for data wrangling in Python. 

Data wrangling is the process of programmatically transforming data into a format that makes it easier to work with. 

This might mean modifying all of the values in a given column in a certain way, or merging multiple columnstogether. The necessity for data wrangling is often a byproduct of poorly collected or presented data. 

In the real world data is messy. Very rarelydo you have nicely cleansed data setsto point your supervised models against. 

Keep in mind that 99% of all applied machine learning (real world machine learning) is supervised.That simply means models need really clean, nicely formatted data.  Bad data in means bad model results out. 

                                                           **Five Reasons to Take this Course**

1) You Want to be a Machine Learning Engineer

It’s one of the most sought after careers in the world. The growth potential career wise is second to none. You want the freedom to move anywhere you’d like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. Without a solid understanding of data wrangling in Python you’ll have a hard time of securing a position as a machine learning engineer. 

2) Most of Machine Learning is Data Wrangling 

If you’re new to this space the one thing many won’t tell you is that much of the job of the data scientist and the machine learning engineer is massaging dirty data into a state where it can be modeled. In the real world data is dirty and before you can build accurate machine learning models you have to clean it. This process is called data wrangling and without this skills set you’ll never get a job as a machine learning engineer.  This course will give you the fundamentals you need to cleanse your data. 

3) The Growth of Data is Insane 

Ninety percent of all the world’s data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month.  Almost all real world machine learning is supervised. That means you point your machine learning models at clean tabular data. Python has libraries that are specific to data cleansing. 

4) Machine Learning in Plain English

Machine learning is one of the hottest careers on the planet and understanding the basics is required to attaining a job as a data engineer.  Google expects data engineers and their machine learning engineers to be able to build machine learning models. 

5) You want to be ahead of the Curve 

The data engineer and machine learning engineer roles are fairly new.  While you’re learning, building your skills and becoming certified you are also the first to be part of this burgeoning field.  You know that the first to be certified means the first to be hired and first to receive the top compensation package. 

Thanks for interest in Data Wrangling in Pandas for Machine Learning Engineers

See you in the course!!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Is this Course for You?

Lecture 3: What is Pandas?

Lecture 4: What is Data Wrangling

Lecture 5: Summary

Lecture 6: Common Interview Questions – Section 1

Chapter 2: Pandas Dataframe Basics

Lecture 1: Download Raw Titanic Data Set

Lecture 2: Load a Data Set in Pandas

Lecture 3: Data Types

Lecture 4: Columns, Rows and Cells

Lecture 5: Using Loc

Lecture 6: iloc and ix

Lecture 7: Subsetting Rows and Columns

Lecture 8: Lab: Slicing Dataframes

Lecture 9: Grouped and Aggregated Calculations

Lecture 10: Grouped frequency counts

Lecture 11: Lab: Grouping

Lecture 12: Summary

Lecture 13: Common Interview Questions – Section 2

Chapter 3: Pandas data structures

Lecture 1: The Series Object

Lecture 2: Series Anatomy

Lecture 3: Lab: Working with the Series Object

Lecture 4: Attributes

Lecture 5: An Array Defined

Lecture 6: The Series and Numpy Array

Lecture 7: Lab: Descriptive Statistics For pandas Dataframe

Lecture 8: Boolean Subsetting with the Series

Lecture 9: Vectorized Operations

Lecture 10: Lab: Row Based Conditional Searches

Lecture 11: Replacing Values in Pandas

Lecture 12: Lab: Saving A Pandas Dataframe As A CSV

Lecture 13: Rename Column Header In Pandas

Lecture 14: Sorting Rows in a Pandas Dataframe

Lecture 15: Read Excel Files

Lecture 16: Regular Expression in Pandas

Lecture 17: Binning Data

Lecture 18: Normalize Data in Pandas

Lecture 19: Lab: Data Normalization

Lecture 20: Data Normalization Lab Line by Line

Lecture 21: Summary

Lecture 22: Common Interview Questions – Section 3

Chapter 4: Introduction to Plotting

Lecture 1: Install Seaborn Via Anaconda

Lecture 2: Matplotlib

Lecture 3: Lab: Matplotlib Basics

Lecture 4: Using Seaborn with a Pandas Dataframe

Lecture 5: Lab: Seaborn Basics

Lecture 6: Summary

Lecture 7: Common Interview Questions – Section 4

Chapter 5: Data Assembly

Lecture 1: File Concatenation

Lecture 2: Row Concatenation

Lecture 3: Lab: Concatenation

Lecture 4: Merging

Lecture 5: Right, Left and Outer Joins

Lecture 6: Lab: Merge Function

Lecture 7: Summary

Lecture 8: Common Interview Questions – Section 5

Chapter 6: Missing Data

Lecture 1: Evaluate Missing Data

Lecture 2: Finding the NaNs

Lecture 3: Dropping out Missing Values

Lecture 4: Dropping Specific Cells

Lecture 5: NaN Value Differences

Lecture 6: Lab: Missing Data

Lecture 7: Filling Using Index Values

Lecture 8: Interpolation of missing values

Lecture 9: Handling Duplicate Data

Lecture 10: Lab: Duplicate Data

Lecture 11: Mapping

Lecture 12: The Replace Function

Lecture 13: Using Functions to Create Columns

Lecture 14: Lab: Breaking Up Strings

Lecture 15: Summary

Lecture 16: Common Interview Questions – Section 6

Chapter 7: Time Series Data

Lecture 1: Time Series Basics

Lecture 2: Timestamp Objects

Lecture 3: Lab: Time Series

Lecture 4: Timedelta

Lecture 5: The DatetimeIndex

Lecture 6: Force Datetime Function with Coerce

Lecture 7: The Frequency Parameter

Lecture 8: Frequency Table

Lecture 9: The DateOffset

Lecture 10: Built-in Date Offset Classes

Lecture 11: Lab: DateOffset

Lecture 12: Anchored Offsets

Lecture 13: Period Object

Lecture 14: Summary

Instructors

Mike West
Creator of LogikBot

Rating Distribution

1 stars: 2 votes

2 stars: 5 votes

3 stars: 19 votes

4 stars: 43 votes

5 stars: 49 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!