Data science courses educate and prepare thousands each year to enter the ever-expanding field of data science. Since we live in a time where much focus is put on electronic and technological advancements, data scientists continue to fill a critical role in helping businesses everywhere find solutions to the problems they face daily. Here we will discuss the vital role data science professionals play in the business world as well as the skills and courses they require to fill this position in an efficient manner.
Syracuse University’s online Master of Science in Applied Data Science program prepares students with advanced data skills for careers in a wide range of industries. Students gain these in-demand skills through collaboration in live online classes and an interdisciplinary curriculum that emphasizes business management, information studies, and data analytics. The program can be completed in 18 months, and GRE scores are not required.Visit Site
The online Master of Information and Data Science (MIDS) program is preparing the next generation of experts and leaders in the data science field and providing students with a UC Berkeley education without having to relocate. Students graduate with connections to UC Berkeley’s extensive alumni network in the Bay Area and across the world. All international applicants will be required to submit official Test of English as a Foreign Language (TOEFL) scores.Visit Site
What are Data Scientists?
Data scientists are experts in gathering, interpreting, and applying vital statistics. They use these statistics to find real-world solutions to common problems that business owners face on a regular basis. Whether they are a small company or a huge retailer, all businesses collect data and use information gathered from it to become more successful and enhance their bottom line. Data science professionals fill an important role when it comes to knowing how to analyze the data gathered to help companies make and save more money while still providing excellent service and superior products.
Overview of Data Science Skills
Data science professionals use many technical and non-technical skills to accomplish their job-related tasks. The following paragraphs cover a few of these basic skills in more detail. We will then discuss the data science courses that teach the understanding and implementation of these data scientist skills.
Some of the most common technical skills that data scientists use include an advanced understanding of calculus and algebra, a thorough understanding of statistics, and a knowledge of the broad array of tools that are used to decipher and analyze the data they extract.
While it is sometimes assumed that data science professionals don’t need these skills since most software is capable of performing those same tasks, having the ability to perform these skills can set one apart from the crowd and give them extra credibility. This may make finding a job or a competitive faculty position much easier.
In addition to sophisticated mathematics skills, having excellent data visualization skills is also very important. Data science professionals also need to be able to decipher current trends and use the data they extract to predict future trends based on current events.
Last but not least, the ability to detect and correct missing or dirty data is also an important skill. Similar to mathematics skills, the ability to not have to rely on machines or software to do this can enhance a person’s career advancement within the field.
Many people fail to recognize that non-technical skills are also necessary when it comes to being successful in the world of data science. For example, professionals within the field must have excellent communication skills. While they have the technical expertise to understand the evaluation of the data that they’ve performed, many times the people they are explaining this information to do not have this same knowledge. Data science professionals must be able to clearly communicate their findings to those at all levels of expertise. This requires excellent communication and interpersonal skills.
Additionally, data scientists need to retain a degree of curiosity and an interest in continuing their education to keep abreast of recent trends and accurately predict upcoming future ones.
Overview of Data Science Courses
There is a wide variety of data science courses that will impart the necessary training and preparation needed to have a successful career in this field. Below we will touch on a few of these courses in more detail.
Data Science Specialization
This course focuses on helping the user fully understand the R programming language. Some basic knowledge of programming is needed before completing this course. A good grasp of basic algebra is also necessary for this course.
Subcategories and specialties that are covered in this course include:
– Obtaining and Cleaning Data
– Conducting Reproducible Research
– Creating Inferences from Statistics
– Creating Regression Models
– Exploring How to Analyze Data Accurately
Machine Learning Specialization
This course teaches the user how to solve real-world problems using specific machine learning techniques. While it requires some pre-existing knowledge of the field, this course teaches the student how to use the Python language to choose the best way to complete a task, design and apply appropriate algorithms, and finalize the cycle through to a workable solution to the problem at hand. Basic calculus and linear algebra are pre-requisites to this course.
Applied Data Science
This course focuses on expanding the student’s skills at working with the Python language to advance their machine learning specialization skills. A degree of programming knowledge and a familiarity with the Python language are necessary prior to completing the course. Ultimately, the result is that the student learns to accurately and efficiently process data.
Statistics with R Specialization
Only basic math is required to get started learning the advanced techniques involved in compiling and understanding statistics. This course teaches the student how to make statistical inferences, how to perform modeling, and how to use visualization techniques to create and understand data reports.
Genomic Data Science Specialization
This course teaches the student the most common genomic technologies and how to apply them to interpret and analyze data from next-generation sequencing experiments. Algorithms for DNA sequencing are an integral part of the course load, with further focus placed on the understanding and using statistics in the area of genomic data science.
As we progress over the next few decades, we are sure to see a continued demand for all types of data science professionals. Both small business and large chains alike rely on collecting, interpreting, and applying all types of statistical data to enhance their success and improve their profit margins. We hope that you have enjoyed this overview of the data science courses that help pave the way for the next set of professionals to provide these skills to the benefit of companies around the world.