TOP 10 DATA SCIENCE COURSES with CERTIFICATIOn IN 2020



By:Dheeraj Verma 
Learning new skills to enhance your abilities to do a task effectively can be a hectic schedule especially if you are an employee. It’s hard to chase coaching or learning centers after spending 8-10 hours in the office per day. And when it comes to becoming technology-efficient specifically in the field of data science, you need to have the best qualification, handy experiences to get better job opportunities in this high in-demand profession. To ease out people’s hectic schedules without compromising with the quality of the education, online platforms like Coursera, Udemy, eDX and many more have a collection of data science certification and courses.

“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”- Hal Varian, chief economist at Google and UC Berkeley professor of information sciences, business, and economics 

WHAT IS DATA SCIENCE ?
Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.


THE DATA SCIENCE LIFE CYCLE 


The image represents the five stages of the data science life cycle: Capture, (data acquisition, data entry, signal reception, data extraction); Maintain (data warehousing, data cleansing, data staging, data processing, data architecture); Process (data mining, clustering/classification, data modeling, data summarization); Analyze (exploratory/confirmatory, predictive analysis, regression, text mining, qualitative analysis); Communicate (data reporting, data visualization, business intelligence, decision making).


The term “data scientist” was coined as recently as 2008 when companies realized the need for data professionals who are skilled in organizing and analyzing massive amounts of data. 1 In a 2009 McKinsey&Company article, Hal Varian, Google's chief economist and UC Berkeley professor of information sciences, business, and economics, predicted the importance of adapting to technology’s influence and reconfiguration of different industries.



Why Become a Data Scientist?

Glassdoor ranked data scientist as the #1 Best Job in America in 2018 for the third year in a row. 4 As increasing amounts of data become more accessible, large tech companies are no longer the only ones in need of data scientists. The growing demand for data science professionals across industries, big and small, is being challenged by a shortage of qualified candidates available to fill the open positions.
The need for data scientists shows no sign of slowing down in the coming years. LinkedIn listed data scientist as one of the most promising jobs in 2017 and 2018, along with multiple data-science-related skills as the most in-demand by companies. 
The statistics listed below represent the significant and growing demand for data scientists.

28%

Demand Increase by 2020

4,524

Number of Job Openings

$120,931

Average Base Salary

#1

Best Job in America 2016, 2017, 2018


Sources: 



 So Here is the list of top 10 best data science 
certification and courses of 2020 prepared by 
DIGITAL DUO.




The certification consists of a series of 9 courses that help students to acquire skills required to work on the projects available in the industry. The lectures span a broad range of topics including data visualization, analysis, libraries, and open-source tools. By the end of the program, the student can showcase his skills and enhance his resume through multiple assignments and projects. During the program, instructors help students to work on the fundamental techniques through examples. Students get plenty of opportunities to implement the skills learned using real-world tools and real-world datasets. Notably, no prior programming or computer science knowledge is required.
Duration: 3 to 5 weeks per course, 2 to 7 hours per week


2.Professional Masters Certificate in 

Data Science – Dartmouth College




This certification program from Thayer School of Engineering is the best option for those who are willing to earn a professional certificate in Data Science by learning all the essential concepts and skills. Students can develop high-demand skills that are required in today’s job market, such as Data Visualization, Machine Learning, Risk Management, and Predictive capabilities. After completion of the course, students will be able to take advantage of new opportunities and face new challenges in the field of Data Science. During the course, students can learn how to create visualizations, build linear and logistic regression models, and apply standard machine learning algorithms. They will work with different projects and develop a data science portfolio at the end of the course that can be shared with employers to showcase their skills.

Duration: 6 months

The University of Michigan School of Information’s online Master of Applied Data Science (MADS) degree is designed for aspiring data scientists to learn and apply skills through hands-on projects. You’ll learn how to use data to improve outcomes and achieve ambitious goals.
The MADS curriculum prepares you to be a leader in the field through mastery of core data science concepts like machine learning and natural language processing. By diving deep on key topics such as privacy, data ethics, and persuasive communication, you’ll be prepared to succeed within today’s organizations. You’ll also work with real data sets from top companies as you build a work portfolio that showcase your skills. Learn the systems and techniques that help organizations overcome data overload and make smart decisions.



4.Machine Learning Certification by Stanford 

University – Coursera





The course has been created by Andrew Ng who is the former head of Google Brain and Baidu AI Group. He has created this along with other professors from Stanford University. In this course, students will learn about Supervised learning, Unsupervised learning among other key areas. The course includes multiple case studies and applications to help students learn how to apply algorithms to build smart robots. It gives a better understanding of parametric and non-parametric algorithms, clustering, dimensionality reduction among other important topics. The students can go through real-world based case studies that will provide the opportunity to understand how problems are solved on a daily basis.
Duration: 55 hour


5.Data Science Certification from Harvard 

University – edX






This program will teach students key data science essentials like R and ML with the help of real-world case studies. It is spread across 9 courses and is rated as among the best online master’s programs available on leading e-learning platform edX. The course spans R Basics, Visualization, Probability, Inference and Modeling, Productivity Tools, Wrangling, Linear Regression, Machine Learning followed by Capstone project to test and try. Students can gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr. They can become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio.

Duration: 9 courses, 2 to 8 weeks per course, 2-4 hours per week

6.MIT Data Science and Statistics Certificate – 

edX




This certification contains a series of 5 courses that will help students strengthen their foundation of data science, statistics and machine learning. They will learn to analyze big data and understand how to make data-driven predictions through statistical inference and probabilistic modeling to extract meaningful data for decision making. To have college-level calculus, mathematical reasoning, and python programming proficiency is advisable. Students may apply to different job roles after the completion of this certification. Students will learn to analyze big data and make data-driven predictions through statistical inference and probabilistic modeling to extract meaningful data for decision making. Students can learn to build machine learning algorithms to make sense of the unstructured data and gain relevant information. They can work on unsupervised learning methods such as clustering methodologies and supervised methods such as deep neural networks.
Duration: 5 courses, 2 to 16 weeks per course


7.Applied Data Science with Python 

Certification – University of Michigan





It is a 5-course program that will help students learn data science through the python programming language. Students need to have basic knowledge of Python and will be taught about popular python toolkits such as pandas, matplotlib, nltk, and networkx. The 5 courses will cover Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python and Applied Social Network Analysis.
Students can go beyond the basics of the Python programming environment including fundamental programming techniques such as lambda, reading and manipulating CSV files and the numpy library. They will learn to work on text mining and manipulation basics.
Duration: 5 months, 7 hours per week


8.Deep Learning Certification – deeplearning.ai





Students can learn how to build neural networks and lead successful machine learning projects through this 5-course specialization. Students will be taught about Python, Tensor Flow, RNNs, LSTM, Adam, Convolutional Networks and Xavier initialization among other aspects. The tutors for this course are Andrew Ng, Co-founder, Coursera & Adjunct Professor, Stanford University; Younes Bensouda Mourri, Mathematical & Computational Sciences, Stanford University, and Kian Katanforoosh, Adjunct Lecturer at Stanford University, deeplearning.ai, Ecole Centrale Paris.

9.Data Science MicroMasters Certification by 

UC San Diego – edX





The course is spread across multiple months and is ideal for students and professionals looking for an immersive learning program that goes deep into the concepts of data science. They will develop a well-rounded understanding of the mathematical and computational tools and how to use them to make data-driven recommendations.  The course covers Python for Data Science, Probability and Statistics, Machine Learning Fundamentals and Big Data Analytics using Spark. Students will use Apache Spark to analyze data that do not fit within the memory of a single computer. They can also work on practical assignments and projects to enhance their portfolio and implement the topics covered in the videos.
Duration: 4 courses, 10-15 weeks per course


10.The Data Science Course 2020: Complete Data

 Science Bootcamp – Udemy





Then topics covered in this course are required to become a successful data scientist. Every topic builds on the previous one and discusses in and out of each of these areas. It allows students to get a better grasp of the facts and figures related to data science. The course provides a complete toolbox to enable students to understand this subject thoroughly. Students can understand the mathematics behind machine learning. They can solve real-life business cases and can start coding in Python. They can also learn how to use it for statistical analysis. The course includes 434 Lectures, 80 Articles, 129, Downloadable resources and full lifetime access.
Duration: 25 hours

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