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Data Science Machine Learning Data mining Coursera Udemy Data Scientist Courses Software Excel

Some Free Online Courses Of Data Science Which Will Make Learning Easier

By ridhigrg |Email | Apr 10, 2019 | 2016 Views

Careers in Data Science A-Z By Udemy
How to Become a Top Level Data Scientist  Learn What to Expect, How to be Prepared, How to Stand Out and More.
Created by Kirill Eremenko, Hadelin de Ponteves

What you will learn
  • The basic steps on how to become a Data Scientist
  • How to take their Data Science career to the next level
  • Hacks, tips & tricks for their Data Science career

Becoming a Data Scientist might be on your mind right now. 
Named the "Sexiest Job of the 21st Century", this career seems like a great idea not only due to its high demand but lack of supply of skilled professionals. 

If you want to get valuable insights, advice, hacks & tips, recommendations, lessons from failures and successes from our careers and learn how to apply it to your own and take your Data Science career to the next level, then this course is just for you.

Data Science Professional Certificate Offered by IBM
Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.

Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning.

This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.

It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, reinforce applied learning, and build up to more complex topics.

Data Science A-Z Real Life Data Science Exercises Included By udemy
Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!

What you'll learn
  • Successfully perform all steps in a complex Data Science project
  • Create Basic Tableau Visualisations
  • Perform Data Mining in Tableau
  • Understand how to apply the ChiSquared statistical test
  • Apply the Ordinary Least Squares method to Create Linear Regressions
  • Assess RSquared for all types of models
  • Assess the Adjusted RSquared for all types of models
  • Create a Simple Linear Regression (SLR)
  • Create a Multiple Linear Regression (MLR)
  • Create Dummy Variables
  • Interpret coefficients of an MLR
  • Read statistical software output for created models

In this course, you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities you name it!

Coursera: Data Science Math Skills Offered By Duke University
Data science courses contain math no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or precalculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one at a time. 
Topics include:
  • Set theory, including Venn diagrams
  • Properties of the real number line
  • Interval notation and algebra with inequalities
  • Uses for summation and Sigma notation
  • Math on the Cartesian (x,y) plane, slope and distance formulas
  • Graphing and describing functions and their inverses on the xy plane,
  • The concept of instantaneous rate of change and tangent lines to a curve
  • Exponents, logarithms, and the natural log function.
  • Probability theory, including Bayes theorem.

While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization.  Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." 

Source: HOB
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