À propos de ce cours : 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.

Les destinataires de ce cours : This course is aimed any anyone in Data Science and has little or no knowledge about the tools used by Data Scientists.

Créé par : IBM

Enseigné par : Polong Lin, Data Scientist

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Informations de base	Cours 2 de 4 dans Introduction to Applied Data Science Specialization
Niveau	Beginner
Engagement	3 weeks of study, 2-3 hours/week
Langue	English
Comment réussir	Réussissez tous les devoirs notés pour terminer le cours.

Programme de cours

SEMAINE 1

Introducing Cognitive Class Labs

This week, you will get an overview of the various data science tools available to you, hosted on Cognitive Class Labs. You will create an account and start exploring some of the features.

4 vidéos, 1 quiz pour s'exercer

Vidéo: Account features
Vidéo: Creating an account
Vidéo: Managing data within My Data
Элемент LTI: Lab - Getting Started with Cognitive Class Labs
Элемент LTI: Lab - Exploring My Data on Cognitive Class Labs
Тренировочный тест: Practice Quiz

Noté: Quiz 1 - Cognitive Class Labs

Jupyter Notebooks

This week, you will learn about a popular data science tool, Jupyter Notebooks, its features, and why they are so popular among data scientists today.

4 vidéos

Vidéo: Getting started with Jupyter
Vidéo: Data and Notebooks in Jupyter
Vidéo: Sharing your Notebooks and Data
Элемент LTI: Lab - Jupyter Notebooks - The Basics
Элемент LTI: Lab - Jupyter Notebooks - More Features
Элемент LTI: Lab - Jupyter Notebooks - Advanced Features
Вопрос для обсуждения: Interesting Jupyter Notebooks on the Internet

Noté: Quiz 2 - Jupyter Notebooks

SEMAINE 2

Apache Zeppelin Notebooks

This week, you will learn about Apache Zeppelin Notebooks, its feature, and how they are different from Jupyter Notebooks.

3 vidéos

Vidéo: Zeppelin for Scala
Vidéo: Getting started with Zeppelin
Элемент LTI: Lab - Zeppelin Notebooks - The Basics
Элемент LTI: Lab - Zeppelin Notebooks - Tutorial

Noté: Quiz 3 - Zeppelin Notebooks

RStudio IDE

This week, you will learn about a popular data science tool used by R programmers. You'll learn about the user interface and how to use its various features.

4 vidéos

Vidéo: Uploading files, Installing packages and loading libraries in RStudio IDE
Vidéo: Getting started with RStudio IDE
Vidéo: RStudio Environment and History
Элемент LTI: Lab - RStudio - The Basics
Элемент LTI: Lab - RStudio - Creating an interactive map in R

Noté: Quiz 4 - RStudio IDE

SEMAINE 3

IBM Data Science Experience

This week, you will learn about an enterprise-ready data science platform by IBM, called Data Science Experience. You'll learn about some of the features and capabilities of what data scientists use in the industry.

4 vidéos, 2 lectures

Материал для самостоятельного изучения: Preface: What is IBM Data Science Experience?
Vidéo: Creating an account on IBM Data Science Experience
Vidéo: Jupyter notebooks on Data Science Experience - Part 1/2
Vidéo: Jupyter Notebooks on Data Science Experience - Part 2/2
Материал для самостоятельного изучения: Lab - IBM Data Science Experience

Noté: Quiz 5 - IBM Data Science Experience

Project: Create and share a Jupyter Notebook

Noté: Create and share your Jupyter Notebook

FAQ

Quand aurai-je accès aux vidéos de cours et aux devoirs ?

Que dois-je faire si j'ai besoin de plus de temps pour terminer le cours ?

À quoi ai-je droit si je paie ce cours ?

Puis-je suivre ce cours gratuitement ?

Quelle est la politique de remboursement ?

Une aide financière est-elle disponible ?

Comment cela fonctionne

Задания курса

Каждый курс — это интерактивный учебник, который содержит видеоматериалы, тесты и проекты.

Помощь сокурсников

Общайтесь с тысячами других учащихся: обсуждайте идеи, материалы курса и помогайте друг другу осваивать новые понятия.

Сертификаты

Получите документы о прохождении курсов и поделитесь своим успехом с друзьями, коллегами и работодателями.

Créateurs

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.

Tarification

	Acheter le cours
Accéder au contenu du cours	Disponible
Accéder au contenu noté	Disponible
Recevoir une Note Finale	Disponible
Obtenir un Certificat de Cours partageable	Disponible