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Data Science with Julia (Part I)

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Data Science with Julia (Part I), available at $54.99, has an average rating of 4.8, with 50 lectures, 15 quizzes, based on 25 reviews, and has 260 subscribers.

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You will learn about Having a strong grasp of data frames in Julia Importing data with Julia Analyzing and manipulating data with Julia Data visualization with Julia This course is ideal for individuals who are You may be an adept data scientist well-versed in Python or R, or you might be embarking on your learning journey, grappling with the choice of a programming language. I will try to convince you that, you can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them. It is particularly useful for You may be an adept data scientist well-versed in Python or R, or you might be embarking on your learning journey, grappling with the choice of a programming language. I will try to convince you that, you can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them.

Enroll now: Data Science with Julia (Part I)

Summary

Title: Data Science with Julia (Part I)

Price: $54.99

Average Rating: 4.8

Number of Lectures: 50

Number of Quizzes: 15

Number of Published Lectures: 50

Number of Published Quizzes: 15

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 65

Original Price: $27.99

Quality Status: approved

Status: Live

What You Will Learn

  • Having a strong grasp of data frames in Julia
  • Importing data with Julia
  • Analyzing and manipulating data with Julia
  • Data visualization with Julia

Who Should Attend

  • You may be an adept data scientist well-versed in Python or R, or you might be embarking on your learning journey, grappling with the choice of a programming language. I will try to convince you that, you can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them.

Target Audiences

  • You may be an adept data scientist well-versed in Python or R, or you might be embarking on your learning journey, grappling with the choice of a programming language. I will try to convince you that, you can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them.

Do you want to learn data analysis, data science, machine learning, deep learning, and AI, but you are not sure about the programming language to choose? Or perhaps you are using Python and R, but you are tired of their slow performance.

You can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them.

Julia is a modern programming language developed for data science, machine learning, AI, and numerical computing. It is a dynamically typed language that is easy to learn and use and moreover has the speed of C.

Julia combines the best features of dynamic languages like Python and R with low-level languages like C, C#, and Java. You can develop a machine learning model or an algorithm in Julia and use that code in a production environment. You don’t have to use different languages for development and production.

This is my second course about Julia. In this course, you will learn how to accomplish essential data science tasks with Julia: importing, analyzing, manipulating, and visualizing data. Having these foundations you will be ready for machine learning and deep learning with Julia which will be in my upcoming lectures. Please stay tuned.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Why use Julia for Data Science?

Lecture 2: Two-Language Problem

Lecture 3: Julia is Fast: Why Does it Matter?

Lecture 4: Is Julia Really Fast?

Lecture 5: Julia Data Ecosystem

Lecture 6: Codes and Resources

Chapter 2: Working with Data Frames

Lecture 1: Creating Data Frames

Lecture 2: Indexing and Slicing Data Frames

Lecture 3: Conditional Filtering

Lecture 4: Selecting and Transforming Columns I

Lecture 5: Selecting and Transforming Columns II

Lecture 6: Summarizing Data with Split Apply Combine Strategy

Lecture 7: Joining Data Frames

Lecture 8: DataFrames: Additional Resources

Chapter 3: Importing Data

Lecture 1: Introduction

Lecture 2: Flat Files

Lecture 3: Delimited Files

Lecture 4: Spreadsheets

Lecture 5: HDF5 Files

Lecture 6: JSON Files

Lecture 7: XML Files

Lecture 8: Relational Databases

Lecture 9: Statistical Programs

Lecture 10: Web Scraping

Chapter 4: Data Analysis & Manipulation

Lecture 1: Introduction

Lecture 2: Project Description

Lecture 3: Import Project Data

Lecture 4: Remove Duplicates

Lecture 5: Merge Input & Output Data

Lecture 6: Summarize Data

Lecture 7: Nonnumerical Data

Lecture 8: Missing Data

Lecture 9: Outliers

Lecture 10: Standardization & Scaling

Lecture 11: Correlation Analysis

Lecture 12: Creating Categorical Variables from Numbers (Optional)

Chapter 5: Data Visualization

Lecture 1: Introduction

Lecture 2: Preparing Data

Lecture 3: Line Plot

Lecture 4: Scatter Plot

Lecture 5: Bar Plot

Lecture 6: Histogram

Lecture 7: Box, Dot, Violin Plots

Lecture 8: Three Dimensional Plots

Lecture 9: Interactive Statsplot

Lecture 10: Makie Package

Lecture 11: Dashboards with Makie

Lecture 12: Observables

Lecture 13: Interactive Dashboards with Makie

Lecture 14: What's Next?

Instructors

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  • 5 stars: 22 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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