Practice Popular Tools and Libraries - 1.3 | 1. Introduction to Advanced Data Science | Data Science Advance
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics

Grades

Grade 8 Grade 9 Grade 10 Grade 11 Grade 12

Curriculum

CBSE ICSE IB
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

games
Typing
Memory
Math
English Adventures
Knowledge

1.3 - Popular Tools and Libraries

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 mock test.

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What library would you use for numerical computations in Python?

💡 Hint: Think about array manipulation and mathematical functions.

Question 2

Easy

Which tool is commonly used for data visualization?

💡 Hint: Consider the importance of displaying data graphically.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

Which library is best for data manipulation in Python?

  • Pandas
  • Matplotlib
  • Scikit-learn

💡 Hint: Think about a library used for cleaning and analyzing data.

Question 2

True or False: TensorFlow is primarily used for traditional machine learning tasks.

  • True
  • False

💡 Hint: Consider the specific tasks TensorFlow is designed to handle.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a predictive model using Scikit-learn that classifies whether an email is spam or not. Detail the steps taken from data preprocessing to model evaluation.

💡 Hint: Remember the importance of cleaning and splitting the data.

Question 2

Using TensorFlow, build a simple feedforward neural network for image classification. Describe the architecture and training process.

💡 Hint: Focus on defining the architecture and the necessary functions for training.

Challenge and get performance evaluation