Python Libraries Skills you will learn

  • Best Python libraries
  • NumPy
  • Pandas
  • Matplotlib
  • Scikitlearn
  • Beautiful Soup
  • TensorFlow

Who should learn this free Python Libraries course?

  • Aspiring data scientists
  • Software engineers
  • Web developers
  • AIML enthusiasts
  • Data analysts

What you will learn in this free Python Libraries course?

  • Python Libraries for Data Science

    • Introduction

      01:18
      • Introduction
        01:18

    • Lesson 1 : Top 5 Python Libraries for Data Science

      15:50
      • Top 5 Python Libraries for Data Science
        15:50

    • Lesson 2 : NumPy Part-1

      30:29
      • NumPy Part-1
        30:29

    • Lesson 3 : NumPy Part-2

      52:40
      • NumPy Part-2
        52:40

    • Lesson 4 : Pandas

      52:38
      • Pandas
        52:38

    • Lesson 5 : Matplotlib Part-1

      35:56
      • Matplotlib Part-1
        35:56

    • Lesson 6 : Matplotlib Part-2

      25:59
      • Matplotlib Part-2
        25:59

    • Lesson 7 : Web Scraping using Python

      37:36
      • Web Scraping using Python
        37:36

    • Lesson 8 : Scikit Learn

      43:58
      • Scikit-Learn
        43:58

    • Lesson 9 : TensorFlow Part-1

      21:18
      • TensorFlow Part-1
        21:18

    • Lesson 10 : TensorFlow Part-2

      43:27
      • TensorFlow Part-2
        43:27

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

Free Course to Learn Python libraries

Why you should learn Python Libraries?

Top skill for 46%

Of job roles in Data Science

$96K

Average salary of a Data Scientist
 

About The Course:

In this course, you'll explore essential Python libraries for data science tasks. These libraries include NumPy, Pandas, Matplotlib, Scikit-Learn, and TensorFlow. NumPy and Pandas are used for data manipulation and analysis, Matplotlib is used for data visualization, Scikit-Learn is used for machine learning algorithms, and TensorFlow is used for deep learning. You'll learn to use these libraries to analyze data, visualize trends, and build machine-learning models. By the end of the Python Libraries course, you'll be equipped with the skills to tackle various data science pro

Read More

FAQs

  • Why should I take a Python libraries course?

    You should take this Python Libraries course to learn essential tools for data science and machine learning. These libraries simplify tasks like data manipulation, analysis, and visualization, making it easier to understand data and build models effectively.

  • What are some common Python libraries covered in these courses?

    This course covers key Python libraries such as NumPy for numerical computations, Pandas for data manipulation, and Matplotlib for data visualization. Additionally, it includes Scikit-Learn for machine learning and TensorFlow for deep learning.

  • Do I need prior programming experience to enroll in a Python libraries course?

    No prior programming experience is needed to enroll in this Python Libraries course. However, having a basic understanding of mathematics, statistics, and data science is recommended. This background will help you grasp the course material more easily.

  • Who should take this Python libraries course?

    This course is ideal for aspiring data scientists, software engineers, web developers, and AI/ML enthusiasts. It's also suitable for data analysts looking to enhance their data science and machine learning skills using Python.

  • How long is the course?

    Python Libraries course is designed to be completed in 7 hours. It provides comprehensive coverage of the essential Python libraries for data science. This duration includes both theoretical and practical learning components.

  • Is there a certification upon completion?

    Yes, you will receive a completion certificate after finishing the course. This certificate validates your proficiency in using key Python libraries for data science. It can enhance your credentials in the job market.

  • How long will I have access to the course materials?

    You will have access to the course materials for 90 days after enrollment. This period allows you ample time to review and practice the concepts learned. Ensure you make the most of this access to reinforce your knowledge.

  • What are the prerequisites for enrolling in this Python libraries course?

    There are no specific prerequisites for enrolling in this Python Libraries course. However, a basic understanding of mathematics, statistics, and data science is recommended. This foundational knowledge will help you grasp the course content more effectively.

Related Courses

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.