Python Libraries For Data Science

Master data science skills with our free course on Python libraries for data science, featuring beginner-friendly videos, exercises, and self-paced learning.
20 Videos
Python
45 exercises
Self Paced

About This Course

Dive into the powerful world of data manipulation with Python libraries for data science 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

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World-class syllabus

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Graded assignments

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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.

$599

$299

Access to course materials

Unlimited

Limited

World-class syllabus

In-demand skills

AI-enabled learning

Graded assignments

Shareable certificate upon completion

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Flexible Mobile Coding

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On-Demand Documentation

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Frequently Asked Questions

Is the Python Libraries for Data Science course free?
Yes, the course is free to access, including all learning materials, videos, and exercises. You only pay if you want to receive a certificate and access additional features through the paid plan.
Do I need any prior experience to enrol in this course?
No prior experience is required. The course is designed for beginners and covers everything from the basics of Python to advanced data manipulation techniques using libraries like NumPy and Pandas.
How long does it take to complete the course, and can I learn at my own pace?
The course is approximately 20 hours long and is fully self-paced. You can learn on your own schedule, making it easy to balance with other commitments.
What specific Python libraries will I learn in this course?
You’ll learn two essential libraries for data science: NumPy, for numerical operations and array manipulation, and Pandas, for data wrangling, analysis, and working with time-series data.
How much does the paid plan cost, and what does it include?
The paid plan costs ₹15,000 and includes additional features such as graded assignments, personalised feedback through AI-enabled learning tools, and a shareable certificate upon completion.
Will I receive a certificate after completing the course?
Yes, if you opt for the paid plan, you will receive a certificate after successfully completing the course. This certificate can be shared on LinkedIn and added to your resume to showcase your skills.
What hands-on exercises and projects are included in the course?
The course includes over 45 exercises that cover data manipulation, array operations, and real-world data wrangling tasks. These exercises are designed to help you build practical skills through applied learning.
How does the free plan differ from the paid plan?
The free plan offers access to all course content, including videos and exercises. The paid plan, in addition to providing a certificate, offers graded assignments, AI-powered feedback, and extended access to course materials beyond the completion date.
What kind of support will I get during the course?
You’ll have access to AI-powered learning tools that provide real-time feedback on your code and progress. For paid users, additional support includes personalised learning paths and evaluation of assignments.
How will this course help me in my career?
By mastering key Python libraries like NumPy and Pandas, you'll gain essential skills for roles in data science, data analytics, and machine learning. The certificate you earn will help you demonstrate your expertise to potential employers and advance your career.
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.

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