Practice Setting Up the Environment - 2 | Python for Data Science | Data Science Basic
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Setting Up the Environment

2 - Setting Up the Environment

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the primary purpose of Anaconda?

💡 Hint: Think about the convenience of having pre-installed tools.

Question 2 Easy

How do you start Jupyter Notebook after installation?

💡 Hint: Recall the command we discussed in class.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does Anaconda provide?

Only Python
Python and essential libraries
A code editor

💡 Hint: Consider what Anaconda includes as a package.

Question 2

True or False: Jupyter Notebook only executes code without any documentation.

True
False

💡 Hint: Remember the features Jupyter offers.

Get performance evaluation

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Create a comprehensive setup plan for a data science project using Anaconda and Jupyter Notebook. Detail the necessary steps and tools you'll utilize.

💡 Hint: Think about the workflow from setup to execution.

Challenge 2 Hard

Analyze the implications of using Anaconda vs. traditional Python package installations for large projects involving multiple contributors.

💡 Hint: Reflect on how package management affects collaboration.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.