What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
Über diesen Kurs
892,363 kürzliche Aufrufe
Karriereergebnisse der Lernenden
36%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
39%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
20%
erhalten Sie eine Gehaltserhöhung oder Beförderung
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 22 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Chinesisch (vereinfacht), Italienisch, Vietnamesisch, Koreanisch, Deutsch, Russisch, Türkisch, Englisch, Spanisch
Karriereergebnisse der Lernenden
36%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
39%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
20%
erhalten Sie eine Gehaltserhöhung oder Beförderung
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 22 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Chinesisch (vereinfacht), Italienisch, Vietnamesisch, Koreanisch, Deutsch, Russisch, Türkisch, Englisch, Spanisch
von
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Lehrplan - Was Sie in diesem Kurs lernen werden
4 Stunden zum Abschließen
Data Scientist's Toolkit
This week, you will get an overview of the programming languages commonly used, including Python, R, Scala, and SQL. You’ll be introduced to the open source and commercial data science tools available. You’ll also learn about the packages, APIs, data sets and models frequently used by data scientists.
4 Stunden zum Abschließen
17 Videos (Gesamt 84 min)
17 Videos
Languages of Data Science2m
Introduction to Python3m
Introduction to R Language3m
Introduction to SQL3m
Other Languages6m
Categories of Data Science Tools2m
Open Source Tools for Data Science - Part 17m
Open Source Tools for Data Science - Part 25m
Commercial Tools for Data Science5m
Cloud Based Tools for Data Science8m
Libraries for Data Science4m
Application Programming Interfaces (API)4m
Data Sets - Powering Data Science6m
Sharing Enterprise Data - Data Asset eXchange3m
Machine Learning Models7m
The Model Asset Exchange5m
4 praktische Übungen
Practice Quiz - Languages 30m
Practice Quiz - Tools30m
Practice Quiz - Packages, APIs, Data Sets, Models30m
Graded Quiz30m
12 Stunden zum Abschließen
Open Source Tools
This week, you will learn about three popular tools used in data science: GitHub, Jupyter Notebooks, and RStudio IDE. You will become familiar with the features of each tool, and what makes these tools so popular among data scientists today.
12 Stunden zum Abschließen
12 Videos (Gesamt 66 min)
12 Videos
GitHub - Getting Started3m
GitHub - Working with Branches5m
Git and GitHub via command line (Optional)9m
Branching and merging via command line (Optional)5m
Contributing to repositories via pull request (Optional)8m
Getting Started with Jupyter Notebook5m
Getting Started with JupyterLab6m
Jupyter Architecture6m
What is RStudio IDE?4m
Installing Packages and Loading Libraries in RStudio IDE2m
Plotting Within RStudio IDE3m
4 praktische Übungen
Practice Quiz - GitHub30m
Practice Quiz - Jupyter Notebook30m
Practice Quiz - RStudio IDE30m
Graded Quiz30m
4 Stunden zum Abschließen
IBM Tools for Data Science
This week, you will learn about an enterprise-ready data science platform by IBM, called Watson Studio. You'll learn about some of the features and capabilities of what data scientists use in the industry. You’ll also learn about other IBM tools used to support data science projects, such as IBM Watson Knowledge Catalog, Data Refinery, and the SPSS Modeler.
4 Stunden zum Abschließen
15 Videos (Gesamt 72 min)
15 Videos
Watson Studio Introduction4m
Creating an Account on IBM Watson Studio2m
Jupyter Notebook in Watson Studio - Part 1 2m
Jupyter Notebook in Watson Studio - Part 23m
Linking GitHub to Watson Studio2m
Other IBM Tools for Data Science1m
IBM Watson Knowledge Catalog6m
Data Refinery7m
SPSS Modeler Flows in Watson Studio6m
IBM SPSS Modeler7m
SPSS Statistics7m
Model Deployment with Watson Machine Learning4m
Auto AI in Watson Studio4m
IBM Watson OpenScale7m
3 praktische Übungen
Practice Quiz - Watson Studio30m
Practice Quiz - Other IBM Tools30m
Graded Quiz30m
3 Stunden zum Abschließen
Final Assignment: Create and Share Your Jupyter Notebook
This week, you will demonstrate your skills by creating and configuring a Jupyter Notebook. As part of your grade for this course, you will share your Jupyter Notebook with your peers for review.
3 Stunden zum Abschließen
1 Lektüre
1 Lektüre
IBM Digital Badge2m
Bewertungen
Top-Bewertungen von TOOLS FOR DATA SCIENCE
von CB1. Nov. 2018
Tools are fantastic and will make a significant contribution to my education. Videos need to be updated for changes to Watson Studios. Support from IBM on their cloud services should also be improved.
von NK19. Mai 2019
The course video contents and the tools versions are not the same.There are some significant differences .Videos should be updated.In general the course is a good fundamental course about the tools.
von RR24. Apr. 2019
To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!
von FD17. Nov. 2020
Some of the lab assignments had instructions that didn't line up with how the programs actually worked. This was particularly the case for modular flow where auto-numerics seemed impossible to use.
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