Is a Data Science Certificate Worth It?

Is a Data Science Certificate Worth It?

A Data Science Certificate alone won’t land you a job—but it will help you build the hands-on experience and professional portfolio you need to be considered for a data science role. The best data science certification programs will teach technical skills through project-based learning, giving you the opportunity to develop an impressive portfolio focused on realistic data science scenarios.

An effective professional certification will focus on the application of data science in business contexts. To get hired in the field, you’ll need to demonstrate solid technical expertise—but that’s not all. You’ll also need to showcase your ability to identify a business problem, frame it as a data science question, and create real-world business impacts through data storytelling. Worthwhile data science certificates will teach you the hard and soft skills you need to become job-ready.

In the age of endless reporting capabilities thanks to innovative software-as-a-service programs, accessing and organizing data from multiple platforms to build a narrative is in demand more than ever. That’s because regularly reporting on hundreds to thousands of data points can be an enormous challenge for businesses. To alleviate the increasing demand for professionals who are trained to research and decipher data, the emerging field of data science can be a rewarding career path.

Earning a data science certificate and acquiring relevant skills are vital for young professionals and businesses to get ahead — and stay ahead — in today’s digital economy.

What is Data Science?

The term “data science” was coined in 2001 by William S. Cleveland, a distinguished professor who specializes in computer science and statistics at Purdue University.

Data science is a board term and incorporates a blend of tools, business acumen, algorithms and machine learning to extract insights and intelligence from raw data. The tools used to analyze and generate predictions range from SAS, Apache Spark, and Tableau. SAS is a leader in business analytics, and the demand for SAS Data Scientists is on the rise. Apache Spark is popular alternative especially companies that are using machine learning models to understand data.

In describing why science is vital to how information is collected and processed, Investopedia states that: “Data science provides meaningful information based on large amounts of complex data or big data. Data science, or data-driven science, combines different fields of work in statistics and computation to interpret data for decision-making purposes.”

From a company’s internal data collection of customers, patients, products or services, to the collection of external data such as traffic on social media, blog posts and product pages, information must be gathered in a way that accelerates business growth. Data science helps to support the corporate vision, strategy, and roadmap.

Professionals interested in Data Science as a career can wear many different titles, such as data analyst, data engineers, and data administrator. There are many data science certification online courses available to help individuals build the skill sets needed to start a successful Data Scientist career. The top Data Science certification online courses are Cloudera Data Scientist, SAP- Fundamentals of Data Science, SAS- Strategies and Concepts for Data Scientists and Business Analysts, and AWS-Practical Data Science with Amazon SageMaker.

Given the speed at which information is accessed and the impact of this on business operations, data science is certainly the wave of the future in 2020 and beyond.

Responsibilities of a Data Scientist

Data scientists do more than just look at numbers on a spreadsheet. The role encompasses a range of skillsets geared toward deciphering large amounts of information or data that can be used to shape quarterly strategies to help businesses grow.

According to Glassdoor, data scientists use their analytical, statistical and programming skills to collect, analyze and interpret large datasets. They then use the information they’ve learned to develop data-driven solutions to overcome difficult business challenges.

One core focus of a data scientist is ensuring businesses have the information they need to effectively communicate to their target audience. This involves storytelling, presentation skills and advanced problem solving.

Get Smarter identifies the following as common responsibilities of a data scientist:

Gather large amounts of unstructured and structured data, then condense it all into a more understandable format

Utilize various programming languages, such as SAS, R and Python, to evaluate performance and other insights from data

Identify trends and patterns in data that may impact profitability

Solve complex challenges using data-driven techniques

Communicate and collaborate with IT and the business as the point of contact

Stay up to date with analytical techniques, such as machine learning, deep learning and text analytics

Earning a Data Science Certificate

As an emerging field, data science is still only in its infancy. The world is expected to generate 50 times more data in 2020 than in 2011, according to SpringPeople. “Considering this, we have no denial to accept the fact that we need conjurers who can maneuver data and create magic with it to drive business growth and innovation.”

Studying to become a data scientist is the first step to embarking on a rewarding career. Earning a data science certificate provides legitimacy that you are sufficient in key skills that will inevitably lead to full-time employment in the field.

Qualifications of a Certified Data Scientist

A Data Science Certificate ensures you possess a broad range of skills that are relevant to countless industries. Throughout a certification program, you’ll learn the following areas of data science to help you become job-ready:

MATH AND STATISTICS

Machine learning

Statistical modeling

Experimental design

Bayesian inference

Optimization

PROGRAMMING AND DATABASE

Computer Science fundamentals

Scripting language: Python

Statistical computing package: R

NoSQL and SQL databases

Algebra

DOMAIN KNOWLEDGE AND SOFT SKILLS

Passion for the business

Data curiosity

Influence without authority

Hacker mindset

Problem-solving techniques

COMMUNICATION AND VISUALIZATION

Ability to engage with senior management

Storytelling skills

Translating data-driven insights into decisions

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Is a Data Science Certificate Worth It?