Data Science uses a combination of computing and data analysis skills to extract insights from large data sets. Being able to recognize previously undiscovered patterns in massive data collections has changed the way how many sciences are done. This makes data science an indispensable subject and data scientists one of the highest paid professions.
The job of the data scientist only emerged in the last few years. Many people currently working in data science are lateral entrants. Data science is perfectly suitable for newcomers.
However, there are many aspects to consider if you want to break into this highly competitive field.
How Can I Break Into Data Science?
It is absolutely possible for newcomers to build a career in data science. You do not even need a background in data analysis. However, you must be aware that this will be a long journey. You need to work systematically and know how to stay motivated.
This is our advice for starting a career in data science:
- Build core foundational skills in programming, statistics and linear algebra. For example, it is an advantage if you are fully confident at handling Python. You also need to know how to use algorithms.
- Progress to advanced methods of machine learning, pattern recognition, data warehousing, and data visualization.
- Start applying those concepts to real-world questions as early as possible. For example, you could conduct a data analysis of healthcare data, find patterns in the preferences of the users of your website, or create your own app. Play around! Applying the skills that you have learned to issues that you feel passionate about enhances your motivation and makes it more likely that you will put in a lot of hours.
- Work with and learn from professionals in the field of data science. Internships are a great way to do this. The comments and feedback that you will be given are invaluable for your learning experience. Internships also help you network and grow your contact base.
- Build a portfolio. Create a portfolio online with your best projects. A good portfolio can be the single most important step to landing your first job.
What Different Ways Exist to Learn Data Science?
You can learn data science in the following ways:
- Take a degree in data science at a university.
- Study from textbooks: There are many textbooks on the internet that you can access free of charge. View this list of 100+ free data science textbooks compiled by the organization LearnDataSci.
- Learn data science with online courses: We currently list 200+ data science online courses in our directory. The following is a list of our favorite 35 online courses in data science. The courses are sorted according to whether they are offered by a university, a corporation, or an online education provider.
1. Data Science Courses Offered by Universities
The following is a list of data science focused online classes provided by universities around the world.
- UCSD “Data Science”-This is a beginner
course that offers a certificate, requires a fee, and teaches you
mathematical and computational skills in order to make data driven business
choices.
- Harvard University “Data Science”- This is a beginner
course that offers a certificate, requires a fee, and offers data
science essentials through real life case studies. Courses include information
on machine learning, probability, visualization, linear regression, R
programming language, and more.
- Johns Hopkins University “Data Science Specialization”- This is a beginner course that offers a certificate, requires a fee, and provides a solid introduction to
data science dealing with topics such as data analysis, receiving data and
organizing data, R programming, machine learning, and statistical inference and
regression.
- University of Michigan “Data Science Ethics”- This is a beginner course that
offers a certificate, does not require a fee, and focuses on ethics in relation
to data science and how to analyze these issues.
- UC Berkeley “Foundations of Data
Science”- This is a beginner course that offers a certificate
option, requires a fee, and provides an introduction to data science with
programming, machine learning, and statistics.
- Massachusetts Institute of Technology “Statistics and Data Science”- This is an intermediate course that offers a certificate option, requires a fee, and provides an
introduction to data science through probability, statistics, machine learning,
and data analysis. Prior knowledge of Calculus and Python programming are
required.
- University of Washington “Communication Data Science Results”- This is an advanced course that offers a certificate option, does not require a fee, and teaches
students to design, recognize, and use visualization in their computer science
research.
- University of Notre Dame “Data Science Readiness Assessment”- This is an intermediate course, in
English, that offers a certificate option, does not require a fee, and helps to
evaluate preparedness in programming and mathematics that are crucial to a
career in data science.
- UC Davis “SQL for Data
Science”- This is a beginner course that offers a certificate
option, does not require a fee, and introduces the fundamentals of SQL and how
to work with data. No prior experience is needed.
- University of Adelaide “Programming for Data Science”- This is a beginner course that offers a certificate option, does not require a fee, and teaches you to
solve real world data problems through data analysis techniques, fundamental
programming concepts, and computational thinking.
- University of Dundee “Data Science in the
Games Industry”- This is an intermediate course that offers a
certificate option, does not require a fee, and looks at how to enhance the
gaming experience and increase profits through the use of big data.
- University of Illinois “Master of Computer Science in Data Science”- This is an intermediate
course that offers a certificate option, requires a fee, and
offers a master’s program which teaches the process of taking statistical and
computational knowledge of big data and how to turn it into perceptive
analysis.
- Wesleyan “Data Analysis
Tools”- This is an intermediate course that offers a certificate
option, does not require a fee, and teaches you how to use the right
statistical test for questions asked to provide a proper data analysis.
- Columbia University “Statistical
Thinking for Data Science and Analytics”- This is a beginner course that offers a certificate option, does not require a fee, and explores
how to judge the probability of an event based on certain conditions.
- University of Colorado “Data Warehouse Concepts, Design, and Data Integration”- This is a beginner
course that offers a certificate option, does not require a fee,
and teaches skills and concepts for creating data workflows and designing data
warehouses.
- Purdue University “AP Computer Science
A: Java Programming Data Structures and Loops”- This is a beginner course that offers a certificate option, does not require a fee, and covers
the basics of programming in Java.
- University of Virginia “Understanding Your Data Analytical Tools”- This is an intermediate
course that offers a certificate option, does not require a fee,
and teaches how to use multilevel analyses based on a real data set. It is
designed for those interested in research methods with SPSS and PhD students.
- IIT Bombay “Foundations of Data
Structures”- This is an intermediate course that offers a
certificate option, does not require a fee, and teaches data structures by organizing
and managing frameworks over time.
- University of Texas at Arlington “Social Network Analysis”- This is a beginner course that
offers a certificate option, does not require a fee, and teaches how to perform
a social network analysis to understand how people share and seek information
in educational settings.
- Hong Kong University of Science and Technology “Introduction to Java Programming Part 1”- This is
a beginner course that offers a certificate option, does not
require a fee, and explores basic Java programming elements along with data
abstraction through object-oriented frameworks and problem representation.
- Imperial College London “Mathematics for Machine Learning Specialization”- This is an intermediate
course that offers a certificate option, requires a fee, and
explores mathematics needed for machine learning and data science
applications.
- Eindhoven University of Technology “Process Mining: Data Science in Action”- This is a beginner course that offers a certificate option, does not require a fee, and provides
data science skills that can be applied to improve and analyze various different
processes.
- Georgia Institute of Technology “Materials, Data Sciences, and Informatics”- This is an advanced course that offers a certificate option, does not require a fee, and
provides an overview of Materials Informatics.
A very informative YouTube video on how to break into data science
