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End to End Python for Data Science Course Overview || Understanding Requirements & Lecture Plan

Whenever we learn something new, 2 things become extremely important

Technical Requirements
Learning Plan

In this video we understand the technical requirements and the lecture plan to have a "Smooth" and "efficient" learning experience

We shall also see the Python for Data Science Course Overview

** Resources:
Link to telegram channel: t.me/+vVOxKAe7VPBiNGU1

Python Libraries for Data Science:    • Complete NUMPY for DATA SCIENCE || Numpy P...  

If you find the course USEFUL, make sure to give a THUMBS UP :)
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Why learn #datascience ??

"Data Science is the sexiest job of 21st century"

If you are a #btech student, #diploma in #computerscience, #graduate looking to #career #tranisition into #datascience , #machinelearning, #dataanalysis, this is a place for you

Everyone of us use social media platforms such as instagram, facebook, or binge watch on OTT platforms such as #youtube , netflix, prime, hotstar or window shop on e-commerce sites such as amazon, flipkart, myntra

It certainly amazes us to see the products of our choice and interest being #recommended to us, our favorite shows being filtered among millions of others

However, not many get to understand how it works. Not to worry, we shall help you understand the concepts in a #simplified and #concise fashion, helping in career transition into machine learning or data science

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Why learn from datahat??

"Datahat is a bridge"
learners --- professionals by simplified data science

It provides a platform to learn, create and collaborate helping in the #career #transition to data science, machine learning and data analysis

Understand the broad domain of data science and its related subdomains in machine learning, data analysis, data engineering in a self paced, #structured and #guided learning

Here are few interesting reads on our blog: medium.com/@souravagarwal54321

Connect with us on linkedIn: www.linkedin.com/company/datahat-unfoldingmystery/

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Additionally, here are few more useful resources for beginners and curious data enthusiasts

1. kaggle: a platform to learn, practice, compete and win cash prizes [www.kaggle.com/]

2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [paperswithcode.com/]

3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [colab.research.google.com/]

Remember, "the greatest #investment ever made is investment in self growth and learning"

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