Data science, analytics, and machine learning are growing at an astronomical rate, and companies are now looking for professionals who can sift through the data gold mine and help them make quick business decisions effectively. IBM predicts that by 2020the number of jobs for all data scientists in the US will increase by 364,000 jobs to 2,720,000. We caught up with Eric Taylor, Sr. Data Scientist at CircleUp, on the Simplilearn Fireside Chat to find out what he’s doing data science, data analytics and machine learning such an exciting field and what skills will help professionals establish themselves in this fast growing domain.

Watch the full Fireside chat recording to find out everything new and exciting about data science, data analytics and machine learning.

Postgraduate Program in Data Science

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What is Data Science?

People have been trying to define data science for over a decade, and the best way to answer the question is through a Venn diagram. Created by Hugh Conway in 2010, this Venn diagram consists of three circles: math and statistics, subject matter expertise (abstraction and computation domain knowledge), and hacking skills. Essentially, if you can do all three, you already have a lot of knowledge in data science.

Data science is a concept used to deal with big data and involves cleaning, preparing and analyzing data. The Data Scientist gathers data from multiple sources and applies machine learning, predictive analytics, and sentiment analysis to extract critical insights from the collected data sets. They understand data from a business perspective and can provide accurate predictions and insights that can be used to make critical business decisions.

Diagram of veins

Venn diagram
source: Drew Conway

Skills needed to become a data scientist

Anyone interested in building a strong career in this field must acquire critical skills in three departments: analytics, programming, and domain knowledge. Going one level deeper, the following skills will help you carve out a niche as a data scientist:

  • Strong knowledge of Python, SAS, R, Scala
  • Hands-on experience in SQL database coding
  • Ability to work with unstructured data from various sources such as video and social media
  • Understand multiple analytics features
  • Machine learning knowledge

What Skills Make a Data Scientist?

Postgraduate Program in Data Analytics

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Postgraduate Program in Data Analytics

What is data analysis?

A data analyst is usually the person who can do basic descriptive statistics, visualize data, and communicate data points for conclusions. They should have a basic understanding of statistics, a perfect feel for databases, the ability to create new views and an understanding of data visualization. Data analytics can be called the required level of data science.

Also Read: How to Become a Data Analyst in 2022?

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Skills needed to become a data analyst

A data analyst must be able to answer a specific question or topic, discuss what the data looks like, and present it to relevant stakeholders within the company. If you want to step into the role of a data analyst, you need to acquire these four key skills:

  • Knowledge of mathematical statistics
  • Fluent understanding of R and Python
  • Data wrangles
  • Understand PIG / HIVE

What are the skills needed to become a data analyst?

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Data Science vs. Data Analytics

Data science is an umbrella term that encompasses data analysis, data mining, machine learning, and several other related disciplines. While a data scientist is expected to predict the future based on past patterns, data analysts extract meaningful insights from a variety of data sources. A data scientist creates questions while a data analyst finds answers to the existing set of questions.

What is machine learning?

Machine learning can be defined as the practice of using algorithms to extract data, learn from it, and then predict future trends about that topic. Traditional machine learning software is statistical analysis and predictive analytics that is used to discover patterns and capture hidden insights based on perceived data.

A good example of applying machine learning is Facebook. Facebook’s machine learning algorithms gather information about each user’s behavior on the social platform. Based on past behavior, the algorithm predicts interests and recommends articles and notifications in the news feed. Similarly, when Amazon recommends products or when Netflix recommends movies based on past behaviors, machine learning is at work.

Skills needed to become a machine learning engineer

What are the skills needed to become a machine learning expert?

Machine learning is simply a different perspective on statistics. The following are critical skills that can help you jump-start your career in this fast-growing field:

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Data Science vs. Machine Learning

Since data science is a broad term for multiple disciplines, machine learning fits into data science. Machine learning uses a variety of techniques, such as regression and supervised clustering. On the other hand, data in data science may or may not evolve from a machine or mechanical process. The main difference between the two is that data science as a broader term not only focuses on algorithms and statistics but also takes care of the entire data processing methodology.

Data science is multidisciplinary

source: Quora

Data science can be seen as incorporating multiple parent disciplines, including data analytics, software engineering, data engineering, machine learning, predictive analytics, data analytics, and more. It involves extracting, collecting, ingesting and transforming large amounts of data known as big data. Data science is responsible for bringing structure to big data, looking for compelling patterns, and advising decision makers to implement change effectively to meet business needs. Data analytics and machine learning are two of the many tools and processes that data science uses.

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Data science, data analytics and machine learning are some of the most in-demand fields in the industry right now. The combination of the right skill sets and real-world experience can help you secure a strong career in these popular fields.

Enroll in our Data Analytics, Data Science, AI and Machine Learning PGP today

If you’re ready to start your journey as a data scientist, data analyst, artificial intelligence and machine learning engineer, the first step is to enroll in an accredited degree program that can prepare you with a Purdue university certificate. Developed in collaboration with IBM, our PG Program in Data Science, PG Program in Data Analytics and AI and ML certification courses teach students everything they need to become skilled professionals. Also check out our Caltech Data Science Bootcamp.

Students in these courses learn all the tools and techniques needed to succeed as a data scientist, data analyst, and machine learning engineer, including SQL databases and core programming languages ​​such as Python and R. Enrollment includes lifetime access to one-on-one crash courses, the opportunity to work on more than 15 real-world projects, $1,200 worth of IBM cloud credits, and more.

Upon completion, students receive industry-recognized university certifications from both Simplilearn and Purdue, which can help them stay one step ahead of the competition. Get started by signing up today!

Data Science vs. Data Analytics vs. Machine Learning

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