DataCamp | Data Analyst VS Data Scientist | Which Career Track to Pick ? | Python | R | SQL | скачать в хорошем качестве

DataCamp | Data Analyst VS Data Scientist | Which Career Track to Pick ? | Python | R | SQL |

https://www.datacamp.com?tap_a=5644-d... An Analysis of the 14 career tracks offered by DataCamp. Making a choice between Data Analyst and Data Scientist in Python with respect to DataCamp Career Paths. So what’s unique about DataCamp? Its primary focus is practicality. You learn by coding! Within each course, you’ll be able to write and execute code directly in your browser without quitting DataCamp. ✅ Check out DataCamp here: https://www.datacamp.com ✅ Read DataCamp review here: https://datasciencerush.com --- Courses in DataCamp Data Science Career Track include: ** Introduction to Python ** You’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. ** Intermediate Python ** You’ll learn to visualize real data with Matplotlib’s functions and get acquainted with data structures such as the dictionary and the pandas DataFrame. ** Introduction to Databases in Python ** You’ll learn the basics of using SQL with Python. This will be useful because databases are ubiquitous and data scientists, analysts, and engineers must interact with them constantly. --- DataCamp is the smart way to lean data science online. You pay monthly fee to gain unlimited access to all the courses on the platform. Interactive courses allow you to code directly within DataCamp, which greatly boosts speed of learning. #datascience #datacamp #datascientist Music by bensound.com ► Social Media   / kit9anks     / ankit-attri999   PYTHON BASICS Introduction to Python, The Scientific Libraries, Advanced Python Programming and the Pandas Section of Data and Empirics https://lectures.quantecon.org/py/ Here are some excellent pandas code examples https://github.com/wesm/pydata-book PRACTICE PYTHON PROJECTS https://github.com/tuvtran/ https://projecteuler.net/ MORE PYTHON Work through as many of the examples as you fancy in Chapters 6 and 7 here https://scipython.com/book/ DATA EXPLORATION https://github.com/StephenElston/ https://www.kaggle.com/c/titanic# PROBABILITY AND STATISTICS https://www.khanacademy.org/math/ http://greenteapress.com/thinkstats/. https://bookboon.com/en/ http://www.wzchen.com/ PYTHON AND DATA SCIENCE https://scikit-learn.org/stable/ DATA STRUCTURES AND ALGORITHMS IN PYTHON https://eu.udacity.com/course/ http://interactivepython.org/ TENSORFLOW https://developers.google.com/ SQL https://www.khanacademy.org/ GIT AND VERSION CONTROL https://git-scm.com/book/en/v2 TAKE THIS CLASS https://cs109.github.io/2015/index.html R https://www.r-bloggers.com/ SUPPLEMENTARY MATERIAL https://docs.python.org/3/tutorial/   / python     / datascience   https://datascience.stackexchange.com/ https://jupyter.org/ SLACK GROUPS: https://kagglenoobs.herokuapp.com/ https://datadiscourse.herokuapp.com/