Torrent details for "Python Hands-On Crash Course For Data Science | 12+ Projects"    Log in to bookmark

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According to StackOverFow report 2020, Python is the most preferred programming language by industry professionals. The report also emphasis that employers prefer Python programmers and are willing to pay them more than any other programming language professionals.

The Harvard Business Review also labelled Data Science and Data Analysis as the Sexiest job of the 21st Century. So imagine if you combine the two(i.e. Python + Data). In my experience at Microsoft working as a Data Scientist, I can testify how software developers, data scientist or data analyst who use Python, become more efficient than others who use other programming languages.

Python is also tagged as the most easiest programming language to learn.

Although, Python has all the attributes of what a good programming language is, if you don’t get to learn it the right way, it can be difficult and boring just like the other programming languages.

In this course, you will learn Python from scratch, right from what is Python till you master the concepts as a professional Python Programmer.

You will gain industry level Python skills needed for Data Analysis, Data Science, Business Analysis, Web development or Machine learning.

This course aims to teach you from beginner level to Python Professional level. I have worked in several companies including Microsoft, Deloitte, and Synacor where I use Python to work on Data, so I know what it takes to be good in Python to land a decent job.

There are lots of exercises, assignments and projects to get you hands-on and comfortable in programming in Python.

This course has been designed and structured inn the following way:

   Get introduced to Python
   Know the various versions of Python
   Set up your coding environment to start coding
   Learn Jupyter Notebook
   Learn Anaconda
   Start to get hands-on by coding in Python
   Learn the various Operators in Python
   Learn the various Flow Controls in Python
   Learn how to handle and debug errors in Python
   Learn Python Modules
   Learn Python Packages and Libraries
   Get to know
       NumPy,
       Pandas,
       Seaborn,
       Matplotlib,
       Plotly,
       Scikit-Learn, etc
   Learn Modern Web Scraping Frameworks like
       Selenium,
       Scrapy,
       Beautiful Soup,
       Request,
       Web drivers, etc
   Build awesome Python Projects
   Learn more Advanced  Machine Learning concepts like
       Linear Regression,
       Logistic Regression,
       KNN,
       Naive Bayes,
       Support Vector Machine, etc
   Build awesome Machine Learning Projects
   Learn Flask
   Create Flask API’s to deploy Machine Learning models live !!

Feel free to check the course curriculum to verify by yourself.

By the end of this course, you will be much confident in programming in Python like a professionals.
Who this course is for:

   Beginners who have never programmed before.
   People Interested In Learning Python For Data Science, Data Analysis, Business Analysis, Machine Learning, Artificial Intelligence, Web Development etc.
   Programmers switching languages to Python.
   If you are interested in learning to code in Python from scratch through building fun and useful projects, then this course is for you!.
   Intermediate Python programmers who want to level up their skills!

Requirements

   No Programming Experience Needed – I’ll teach you everything you need to know from scratch
   No Paid Software Required – I’ll teach you how to use PyCharm, Sublime Text, Jupyter Notebooks, Flask and Google Colab.
   A Windows Laptop, Mac, PC or Linux computer with access to the internet
   I’ll walk you through, step-by-step how to get all the software installed and set up
   I’ll walk you through, step-by-step all the concepts and how to use the softwares.
   Your enthusiasm to learn !!

Last Updated 7/2021

  User comments    Sort newest first

by Guest-6480
    on 2021-11-18 13:55:03
avatarHey mate, Thanks for the upload, Most of the videos are corrupt. Some folders are also missing.
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