Free Course
Python

Python Libraries For Data Science

Master data science skills with our free course on Python libraries, featuring beginner-friendly videos, exercises, and self-paced learning.
20 videos
No Coding Experience Required
45 exercises
Self Paced
Certification available
20 Hours
Duration
Beginner
Skill Level
None
Requirements
Included With Paid Plan
Certificate
Program Overview

Dive into the powerful world of data manipulation with Python libraries like NumPy and Pandas. Explore how to efficiently work with multidimensional arrays, perform data wrangling operations, and analyze large datasets. These skills are crucial for anyone aspiring to become a data scientist, data analyst, or machine learning engineer.

Learn at your pace
Step-by-step guidance
Hands-on exercises
What You'll Learn
  • Build a solid foundation in Python programming from scratch
  • Efficiently manipulate data using NumPy and Pandas
  • Understand and create multidimensional arrays
  • Master various indexing techniques for data manipulation
  • Perform complex array operations and transformations 
  • Slice and dice data for targeted analysis 
  • Reshape and transform arrays for diverse applications
  • Apply linear algebra concepts with NumPy for data science 
  • Differentiate between Pandas and NumPy for specific tasks 
  • Leverage Python libraries to tackle real-world data problems

Syllabus
Lesson 1: Introduction to Numpy

Understand the power of Numpy for numerical computing in Python, enabling efficient handling of large arrays and matrices.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 3:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 2: Difference between List and Numpy Array

Learn the distinctions between Python lists and Numpy arrays, highlighting Numpy's superior performance and functionality for numerical operations.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 3:20 mins

Assignment · 5 mins

Lesson 3: How to create Multidimensional Array

Master the creation of multidimensional arrays in Numpy, essential for representing and manipulating multidimensional data structures.

Array · 4:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 4: Operations on Array

Explore various mathematical and logical operations that can be performed on Numpy arrays, facilitating complex computations and data transformations.

Lesson 5: Indexing

Understand different indexing techniques in Numpy arrays, allowing efficient access to specific elements or subsets of data.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 6: Slicing and Dicing

Learn to slice and dice Numpy arrays to extract relevant portions of data, crucial for data analysis and manipulation tasks.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 7: Indexing with Boolean Array

Utilize boolean arrays for advanced indexing in Numpy, enabling conditional selection and filtering of data elements.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 8: Arrange Function

Discover the arrange function in Numpy for generating arrays with evenly spaced values, facilitating numerical operations and data generation.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 9: Universal Function on Array

Explore universal functions (ufuncs) in Numpy for element-wise array operations, optimizing performance and code readability.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 10: Shape Manipulation Function

Master shape manipulation functions in Numpy for reshaping, resizing, and transforming array dimensions as needed for various data processing tasks.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 11: Broadcasting

Understand broadcasting in Numpy for performing operations on arrays with different shapes, simplifying code and improving performance.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 12: Linear Algebra

Gain proficiency in linear algebra operations with Numpy, including matrix multiplication, decomposition, and solving linear equations, crucial for data science and machine learning applications.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 13: Pandas

Dive into Pandas, a powerful data manipulation library in Python, for efficient data analysis and manipulation.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Lesson 14: Difference between Pandas and Numpy

Understand the distinctions between Pandas and Numpy, highlighting Pandas' specialization in data manipulation tasks with labeled axes.

Course Introduction · 4:20 mins

Getting Started · 5:20 mins

Project · 5:20 mins

Assignment · 5 mins

Quiz · 5 mins

Certificate

Free

How would you like to
take this course?

You can choose to be certified or take the course for free.
Decide when you apply.

Apply Now

₹ 15,000

-

Course Fees

Access to course materials

Limited

Limited until course completion

World-class syllabus

In-demand skills

AI-enabled learning

Graded assignments

Shareable certificate upon completion

Frequently Asked Questions
What technologies will I learn in the Data Science bootcamps?
A1: You will learn Python, R, SQL, Power BI, Tableau, Excel, Pandas, Numpy, Matplotlib, Seaborn, and PySpark.
Can I start with no prior experience in Data Science?
Yes, our programs are designed for both beginners and those looking to deepen their knowledge. We offer fundamental courses as well as advanced bootcamps.
What is the duration of your Data Science bootcamps?
Our bootcamps are designed to be completed in 4 months with a focus on real-world applications in the banking and finance sectors.
How is the curriculum for the Data Science bootcamp structured?
The curriculum includes hands-on projects, case studies focused on the banking and finance industry, and courses on core data analysis tools and techniques.
Will I have access to the course materials after the bootcamp is over?
Yes, you will have lifetime access to all course materials, which you can refer to at any time to refresh your knowledge or tackle new challenges.
 What type of job support do you provide after completing the course?
We offer comprehensive placement assistance, including resume building, mock interviews, and leveraging our network of industry partners.
How do you prepare students for the job market?
We equip students with industry-relevant skills, help craft winning resumes, and provide mock interview practice with experienced mentors.
Do you guarantee a job after completing the course?
While we do not guarantee a job, we provide extensive support to help you become highly competitive in the job market.
 Can you help me find a job in any specific industry?
Our job assistance is generalized; we prepare you for a variety of roles in the data science field rather than focusing on specific industries.
What is the cost of the Data Science bootcamp?
The cost varies depending on the program. Our full bootcamp is priced between ₹50,000 and ₹75,000, depending on whether you choose self-paced or live instruction.
 Are scholarships available for the courses?
Yes, we offer scholarships that can cover up to 70% of the tuition fees, making our courses more accessible to a wider range of students.
What is included in the course fee?
The fee includes access to all course materials, live coding sessions, AI-based learning platform, case studies, capstone projects, and mentorship from industry experts.
What payment options are available for the course fees?
We offer flexible payment options, including easy EMIs, and you can cancel anytime in the first 7 days for a full refund.
Is financial aid or other support available aside from scholarships?
While our primary financial support is through scholarships, our enrollment advisors can also assist you with payment plans and financing options to help manage the cost of your education.
Join over 8 million highly paid developers. Start learning Python today!
Start Free Course