Data science combines statistics, scientific methods, machine learning and data analysis concepts with a goal of extracting value from raw data. Data scientists collect data from a wide variety of sources, including customers, the internet, supply chains, operational data, sensors, smartphones and any other relevant sources, to determine actionable insights.
Data science helps reveal emerging trends, produces key insights that can be used to inform better decision making and is key to the development of technology for many industries, including the creation of innovative products and services. For example, recommendation systems leverage data to optimize product experiences.
How do I start learning data science?
An understanding of data, the scientific method, statistics, mathematics, communication and programming languages are required for data science competency.
To become a data scientist, a thorough understanding of data, databases, statistics, visualization, the scientific method, mathematics (such as linear algebra) and a programming language, such as Python, is required.
Additionally, understanding machine learning, forecasting, deep learning and natural language processing concepts are crucial to becoming a highly capable data scientist. Most importantly, data scientists must have the ability to communicate with stakeholders, accurately answer questions and resolve hypotheses through the creative use of data.
Finally, there are a number of bootcamps, classes and certifications available for a wide variety of skill sets, whether you're just looking to understand basic data science concepts or start a new career as a data scientist.
What can I do with a data science degree?
Data scientists are in demand at just about every organization on the planet, with many entry-level positions available in multiple industries.
Data science has a bevy of potential applications for private companies, non-profits, government sector jobs and others, making the demand for data scientists higher than ever. Often, data scientists will also be tasked with storing, wrangling and mining data, filling a data engineering role. With this base of data, data engineers and scientists play an instrumental role in developing technology and creating new products. Additionally, data scientists play a huge role in organizational value by providing traffic, product performance, customer interaction, market growth, sales figures, churn and additional metrics, helping stakeholders make better decisions based on the likelihood of an outcome. As data creation and storage capabilities continue to grow rapidly, the need for data scientists will also increase exponentially.
As data scientists continue to develop and gain experience in their careers, they will begin to undertake projects such as creating machine learning models and managing data science teams in day-to-day operations. According to the U.S. Bureau of Labor Statistics, data scientists and mathematical science occupations offered a median annual wage of $98,230 in 2020, with the lowest 10% making an average $52,950 and the highest 10% making an average of $165,230.
Can I learn data science on my own?
The basics of data science can be learned by taking a variety of online courses and by studying several resources.
Data science is a highly technical discipline, requiring those studying it to develop a working knowledge of concepts like machine learning, data mining, business intelligence, programming and more. Forming a career as a data scientist requires a formal education and years of work experience as a data analyst or a similar role, however, several courses and certifications are available online to kickstart your journey. Udemy offers a wide variety of online courses created by data science experts. Courses are aimed at both professionals looking to fill specific skill gaps or beginners looking to understand data science basics. Those new to data science should begin by looking for Udemy data science bootcamp courses, which will provide a full understanding of data science basics and necessary skills with real-world training scenarios in a fast-paced environment.
Udacity also offers several training options in a more formal online education setting that provides a certification in the form of a “nanodegree” at the end of their courses. While Udacity’s courses are often focused on a specific facet of data science, such as working with SQL or data visualization, they present those with some background knowledge with an opportunity to improve in key areas while receiving a nanodegree certification that can add tremendous value to any resume. Additionally, Built In’s expert contributor network has built a library of material from real-world perspectives that can provide insight into how working data science professionals and academic researchers do data science on a daily basis.”
