Data Science Courses with high-level Certifications

Fundamental R programming skills
Statistical concepts such as probability, inference, and modeling and how to apply them in practice
Gain experience with the tidy verse, including data visualization with ggplot2 and data wrangling with dplyr
Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio
Implement machine learning algorithms
In-depth knowledge of fundamental data science concepts through motivating real-world case studies

Professional Certificate in Python Data Science

IBM

What you will learn

Understand Python language basics and apply to data science
Practice iterative data science using Jupyter notebooks on IBM Cloud
Analyze data using Python libraries like pandas and numpy
Create stunning data visualizations with matplotlib, folium and seaborn
Build machine learning models using scipy and sci-kit learn
Demonstrate proficiency in solving real-life data science problems

Analyzing Data with Python

In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using sci-kit-learn!

IBM

About this course

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!

Data Science: R Basics

Build a foundation in R and learn how to wrangle, analyze, and visualize data.

Harvard University

About this course

The first in our Professional Certificate Program in Data Science, this course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you'll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states.

We'll cover R's functions and data types, then tackle how to operate on vectors and when to use advanced functions like sorting. You'll learn how to apply general programming features like "if-else," and "for loop" commands, and how to wrangle, analyze and visualize data.

Rather than covering every R skill, you might need, you'll build a strong foundation to prepare you for the more in-depth courses later in the series, where we cover concepts like probability, inference, regression, and machine learning. We help you develop a skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.

Source: HOB

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