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100% Discount || NumPy & Pandas Masterclass for data analysis and ML | 2023

NumPy & Pandas Masterclass for data analysis and ML | 2023

Requirements

  • Basic Python

Description

***** Enrol now in the most comprehensive and up-to-date (Nov 2022) course available for the NumPy & Pandas Concepts! *****

About the Instructor.

This course is led by Aditya Dhandi – an international trainer, consultant, and data analyst with over 100 000 enrollments on Udemy. Aditya specializes in teaching data analysis techniques, Excel Pivot Tables, Power Pivot, Microsoft Power BI, & Google Data Studio & his courses average 4+ stars out of 5.

He’s also the founder of the popular website, Jobshie.

Why Learn Numpy?

The central object in Numpy is the Numpy array, on which you can do various operations.

The key is that a Numpy array isn’t just a regular array you’d see in a language like Java or C++, but instead is like a mathematical object like a vector or a matrix.

That means you can do vector and matrix operations like addition, subtraction, and multiplication.

The most important aspect of Numpy arrays is that they are optimized for speed. So we’re going to do a demo where I prove to you that using a Numpy vectorized operation is faster than using a Python list.

Then we’ll look at some more complicated matrix operations, like products, inverses, determinants, and solving linear systems.

Why learn pandas?

If you’ve spent time in a spreadsheet software like MS Excel or Google Sheets and want to take your data analysis skills to the next level, this course is for you!

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python.

Pandas is the most powerful and flexible open source data analysis/manipulation tool available in any language.

pandas is well suited for many different kinds of data:

  • Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet
  • Ordered and unordered (not necessarily fixed-frequency) time series data.
  • Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels
  • Any other form of observational / statistical data sets. The data need not be labeled at all to be placed into a pandas data structure

Key Features:

Video Lectures: Learn the best ways to learn NumPy & Pandas

Course Certificate: Complete the course and show off your skills with the course certificate.

Learn from experts: Your expert instructor will teach you NumPy & Pandas skills you can apply immediately.

Full Excess: There is no time limit, so take the course at your own pace and retake lessons as you need.

Use any Device: Join the course using any modern browser on your phone, tablet and computer.

Ask Question: Ask questions and share ideas with other students in the course community.

What’s included?

  • High quality video lessons to build your knowledge and skills.
  • Guided walk-throughs with techniques and tips.
  • 14 pre-built dashboards you can use and customize.
  • Practical exercises to apply your skills.
  • Quizzes to reinforce learnings and test your knowledge.
  • Private discussion area where you can ask questions.
  • Course certificate for completing the lessons and assignment.
  • Full access lets you review lessons whenever you need.
  • Updates when lessons in the course are refreshed.

Jobshie Academy Reviews

300+ learner reviews | 4+ average rating

We help learners across the globe develop new skills and achieve their personal and professional goals. Browse learner reviews below to discover how people enjoy the online learning experience at Jobshie Academy.

“I have gained useful skills while learning this course. I can consider myself a data analysis specialist. Thank you”

by Joseph Israel

“I was a nice experience about this course as it introduces with many topics which are related to data analysis .”

by Sreeraj Mopkar

“very good explaination , bohot achhe se sab samajh aata hai …100% Understanding all concept very much….excellent explanation”

by Moosa Khan

“The course is very instructive and didactic, I liked it, it is all the information I need for my activities”

by Jaime Ronald Palma Aguilar

“yeah it was such a great course, the teacher took time out to disect all angles of Excel, he touched all the essential parts, needed for our daily use of excel. Thanks a lot”

by Unyime Joshua

“The instructor is very knowledgeable and teach in a very engaging way. I totally recommend this course.????”

by Aditya

FAQs

When does the NumPy & Pandas course start and finish?

The course starts as soon as you join! It is a completely self-paced online course, so you decide when you start and when you finish.

How long does it take to complete the course?

We recommend taking the course over two to three weeks, so you have time to apply the lessons to your account (or your client’s account). That being said we’ve seen people complete the course in a week and others that spread the lessons over a couple of months.

How long do I have access to the NumPy & Pandas course?

You receive full access to the course so that you can take the lessons at any time. You can rewatch lessons whenever you like and any lesson updates are included.

Will I receive a certificate?

Yes, once you complete all of the lessons, exercises, quizzes, and course assignment, you’ll receive your course certificate.

What are you waiting for?

There’s never been a better time to add a skill like programming to your toolbox and NumPy & Pandas to get started. So check out the free preview and get enrolled! You’ve got nothing to lose and everything to gain!

Who this course is for:

  • Students and professionals who wants to do data analysis using python.
  • Python developer who wants to do analysis of tabular data.
  • Students and professionals with little Numpy experience who plan to learn deep learning and machine learning later
  • Students and professionals who have tried machine learning and data science but are having trouble putting the ideas down in code


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