Ways to revive your career in Data Science

This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you'll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

WHAT YOU WILL LEARN

Use R to clean, analyze, and visualize data.
Navigate the entire data science pipeline from data acquisition to publication.
Use GitHub to manage data science projects.
Perform regression analysis, least squares, and inference using regression models.

Applied Data Science Specialization

Offered By IBM

Get hands-on skills for a Career in Data Science. Learn Python, analyze and visualize data. Apply your skills to data science and machine learning.

This is an action-packed specialization is for data science enthusiasts who want to acquire practical skills for real-world data problems. It appeals to anyone interested in pursuing a career in Data Science and already has foundational skills (or has completed the Introduction to Applied Data Science specialization). You will learn Python - no prior programming knowledge necessary. You will then learn data visualization and data analysis. Through our guided lectures, labs, and projects you'll get hands-on experience tackling interesting data problems. Make sure to take this specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning.

Upon completing all courses in the specialization and receiving the Specialization certificate, you will also receive an IBM Badge recognizing you as a Specialist in Applied Data Science.

Introduction to Data Science in Python

Offered By University of Michigan

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating CSV files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as group by, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

WHAT YOU WILL LEARN

Describe common Python functionality and features used for data science
Explain distributions, sampling, and t-tests
Query DataFrame structures for cleaning and processing
Understand techniques such as lambdas and manipulating CSV files

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 pre-calculus. 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.

Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material.

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 x-y 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.

Executive Data Science Specialization

Offered By Johns Hopkins University

Be The Leader Your Data Team Needs. Learn to lead a data science team that generates first-rate analyses in four courses.

In four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You'll get a crash course in data science so that you'll be conversant in the field and understand your role as a leader. You'll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you'll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.

WHAT YOU WILL LEARN

Become conversant in the field and understand your role as a leader.
Recruit, assemble, evaluate, and develop a team with complementary skill sets and roles.
Navigate the structure of the data science pipeline by understanding the goals of each stage and keeping your team on target throughout.
Overcome the common challenges that frequently derail data science projects.

Source: HOB

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