Packt – Mathematics for Data Science and Machine Learning using R

Packt – Mathematics for Data Science and Machine Learning using R-XQZT
English | Size: 3.19 GB
Category: Tutorial

With data increasing every day, Data Science has become one of the most essential aspects in most fields. From healthcare to business, data is essential everywhere. However, it revolves around three major aspects: data itself, foundational concepts, and programming languages that interpret data.
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Linkedin – Learning R Programming in Data Science Dates and Times

Linkedin – Learning R Programming in Data Science Dates and Times-BiFiSO
English | Size: 781.72 MB
Category: CBTs


Join author Barton Poulson as he introduces the R statistical processing language, including how to install R on your computer, read data from SPSS and spreadsheets, and use packages for advanced R functions. [Read more…]

Lynda – R Programming in Data Science – Dates and Times

Lynda – R Programming in Data Science- Dates and Times
English | Size: 322.06 MB
Category: Tutorial


Author
image of author Mark Niemann-Ross
Mark Niemann-Ross
Released7/24/2019
One of the fundamental difficulties of data science is working with dates and times. This course shows data engineers, DevOps practitioners, and data-science programmers the most common (and many not so common!) problems and how to use R-based tools to implement solutions. Learn how dates and times are stored and retrieved in base R. Find out how to format, compare, add and subtract, and extract dates and times using built-in R functions. Then discover how to incorporate specialized R packages, such as lubridate, busdater, zoo, timelineR, anytime, datetime, and more, to perform some of the heavy lifting. Instructor Mark Niemann-Ross walks you through each package, so you can appreciate the advantages and best uses of each one. [Read more…]

Udacity – Programming for Data Science v1 0 0

Udacity – Programming for Data Science v1 0 0
English | Size: 2.21 GB
Category: Tutorial


Programming for Data Science
Prepare for a data science career by learning the fundamental data programming tools: Python or R, SQL, command line, and git. Choose to enroll in either the Python or R track.

Learn to Code in Python and SQL
Learn the programming fundamentals required for a career in data science. By the end of the program, you will be able to use Python, SQL, Command Line, and Git. [Read more…]

SKILLSHARE Cybersecurity Data Science – iLLiTERATE

SKILLSHARE CYBERSECURITY DATA SCIENCE-iLLiTERATE
English | Size: 351.88 MB
Category: Tutorial


The best of the best badass hackers and security experts are using machine learning to break and secure systems. This course has everything you need to join their ranks.

In this one-of-its-kind course, we will be covering all from the fundamentals of cybersecurity data science, to the state of the art. We will be setting up a cybersecurity lab, building classifiers to detect malware, training deep neural networks and even breaking CAPTCHA systems using machine learning.
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[Pluralsight] Boost Data Science Productivity with PyCharm

[Pluralsight] Boost Data Science Productivity with PyCharm
English | Size: 426.74 MB
Category: CBTs

Being productive with the tools at your disposal is key to the success of any data scientist. Pycharm brings many coding, debugging, and scientific tools to the table. In this course, Boost Data Science Productivity with PyCharm, you will gain the ability to use PyCharm’s most relevant features for Data Science projects. Features such as highlighting typos and visual debugging reduce development friction and empower you to focus on finishing your Data Science projects faster. First, you will learn to understand code faster, by finding usages, creating classes diagrams, viewing hierarchies, and accessing documentation. Next, you will discover how to write better code faster by using PyCharm features, such as code completion, refactoring, and inspections, as well as how to debug code by using breakpoints, stepping, and remote debugging. Finally, you will learn how to explore data by using the scientific mode in PyCharm, Jupyter notebooks, running R script, and SQL queries. When you’re finished with this course, you will have a great set of tips, tricks, and techniques to boost your Python productivity in your Data Science projects. [Read more…]

[Packt] Python and Data Science A Practical Guide

[Packt] Python and Data Science A Practical Guide
English | Size: 3.12 GB
Category: CBTs

Date Of Publication 29 Mar 2019
Course Length 13 hours 9 minutes

Learn

How to set up your Python environment
How to manipulate String & Variables with Python
How to use Booleans & Logical Operators with Python
How to use Functions & Packages with Python
How to use Pandas & Data Frames with Python
How to perform Data Visualization with Python
How to do Web Scraping with Python
The Basics of Natural Language Processing (NLP)
The Basics of Deep Learning & Reinforcement Learning
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Packt Python And Data Science A Practical Guide

Packt Python And Data Science A Practical Guide
English | Size: 2.90 GB
Category: Tutorial

This course is designed to teach you the basics of Python and Data Science in a practical way, so that you can acquire, test, and master your Python skills gradually.
You’ll see that you’ll learn all these things with Python:
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Skillshare Essentials Of Data Science

Skillshare Essentials Of Data Science
English | Size: 545.30 MB
Category: Tutorial

Data Science is growing ever faster as Big Data become an increasingly important part of our lives.
Because data is universal, the applications of Data Science are pretty much endless, all you need is access to the data of the system that you want to study.

Since it’s such a new field, there are a lot of questions about what is Data Science, what do Data Scientists do, and what do you need to succeed as a Data Scientist? [Read more…]

LiveLesssons – Data Science Fundamentals Part 1

LiveLesssons – Data Science Fundamentals Part 1
English | Size: 5.69 GB
Category: Programming

Data Science Fundamentals LiveLessons teaches you the foundational concepts, theory, and techniques you need to know to become an effective data scientist. The videos present you with applied, example-driven lessons in Python and its associated ecosystem of libraries, where you get your hands dirty with real datasets and see real results.
Description
If nothing else, by the end of this video course you will have analyzed a number of datasets from the wild, built a handful of applications, and applied machine learning algorithms in meaningful ways to get real results. And along the way you learn the best practices and computational techniques used by a professional data scientist. More specifically, you learn how to acquire data that is openly accessible on the Internet by working with APIs. You learn how to parse XML and JSON data to load it into a relational database. [Read more…]