Your Guide for Online Data Science Courses in 2021
Data scientists work with large amounts of complex data to help improve outcomes for their organizations. They process and analyze the data to derive meaningful, actionable information from it. These interpretations are then used for analysis and decision-making purposes that can be applied within a multitude of work environments.
If you’re interested in becoming a data scientist, it may be useful to complete a data science course. For students who wish to study from home or part time for any reason, taking an online data science course could be a possible option.
Finding the Best Data Science Courses Online for You
Finding the best data science short courses, including the best online data courses, depends as much on the course content as it does on you. When looking for a data science course, you may want to consider your education, which skills you want to learn and the direction you plan on taking your career. For some careers, data science short courses would be adequate, while others might warrant more in-depth training.
What Are Data Science Course Online Topics?
Data science courses’ curriculums vary depending on what you choose to focus on. Some data science courses focus on an overview. In contrast, others consist of more in-depth coverage of subcategories within the field. An in-depth data science course would likely cover more than one subdivision, while data science short courses typically focus on only one, or perhaps two, subdivisions.
The common topics included in data science courses curriculums cover:
- Statistics — deals with collecting and analyzing numerical data in order to draw usable conclusions from it. This subdivision includes probability (i.e., using data to predict the likelihood of something).
- Calculus — the study of rate of change that allows for analysis of quantitative models of change in order to infer consequences from them.
- Linear algebra — a branch of mathematics that deals with data.
- Programming — focuses on writing code; this is often used to automate data processing.
- Machine learning — sometimes relates to artificial intelligence (i.e., the science of engineering intelligent machines). This niche of data science teaches computers to program themselves for specific tasks, and this subdivision includes deep learning.
- Data mining — analyzing data to extract important and relevant information.
- Data visualization — the representation of data in images or charts.
Data Science Courses vs. Certificates
Data science courses offer short courses vary based on what you’re interested in learning. Topics may include machine learning, artificial intelligence, programming in Python or R, and data mining. Courses may take less time than the average graduate certificate programs to complete. Some data science courses take as few as 10 hours to complete and can be done online.
Data science graduate certificate programs usually concentrate on one or two subtopics within data science. Graduate certificate programs in data science typically comprise 12 credit hours. In some cases, the courses offered as part of a certificate program count toward a master’s in data science degree. That means if you have completed one (or more) certificate programs in data science, you may not need to redo these sections if you decide to complete a master’s in data science degree
Whether you decide to complete a data science graduate certificate or a master’s in data science degree may depend on several factors. Consider your educational background, how much time you can dedicate to your studies and your career goals when making this decision.
Certificate in Business Analytics
Harvard’s 9-month certificate program equips high-level executives with the data and analytics skill set to lead their organizations to the industry forefront.
- Live online classes in a webcam-enabled online classroom
- Case-based lessons pioneered by Harvard Business School (HBS) faculty
- In-person learning experiences at immersions hosted on Harvard Business School’s campus in Boston
Is an Online Data Science Course Worth It?
Online learning programs help students obtain knowledge and skills from home and in their own time. The deliverables of data science short courses vary from course to course. Some may require a larger time commitment, while others could include project-based learning that provides valuable experience that you can transfer to your work environment. The best data science courses online for you could give you all the benefits that you would get from completing a traditional in-person course, with some added benefits.
Some benefits to taking an online data science course include:
- The flexibility to select which topics you would like to focus on if you want to niche down.
- Self-paced studying.
- Learning additional skills without the commitment or expense of a master’s in data science degree.
- Add to your skill set in a relatively short time.
- Access to online communities related to your area of interest.
Data Science Course Duration
Data science courses vary widely in duration and depend on the complexity and breadth of information that needs to be covered. This is sometimes true for data science short courses, as they cover a wide range of niche topics.
Many courses may take 10 or more hours to complete. These relatively shorter courses offer you the flexibility to build a new skill set and gain additional knowledge without committing to a full master’s degree in data science. In contrast to data science short courses, a master’s degree in data science often takes between one and two years to complete.
Your current skills and knowledge may have an impact on the amount of time required to complete the course, as will the complexity of the topic at hand. Some courses may take at least one week to complete, while others may offer a recommended time commitment of at least one hour per week for data science short courses.
Skills You Learn From a Data Science Course
Data science courses cover a variety of topics and equip students with various skills. These may include:
- Programming languages such as Python and R, as well as SQL.
- Structuring the data science process, defining a problem and interpreting results.
- Collecting and organizing data in a useful format through data acquisition, cleaning, storage and access.
- Analyzing massive amounts of raw and processed data to identify patterns that could influence strategic business decisions.
- Creating data funnels and automation programs and software solutions.
- Building machine learning systems, running tests and maintaining and monitoring them.
- Researching new data approaches and algorithms that can be used in adaptive systems.
- Using data to tell a story that convinces stakeholders and leads to decisions.
- Creating new database systems.
- Improving the performance and functionality of existing data systems.
- Performing batch processing or real-time processing on stored data.
- Building and maintaining data pipelines.
- Designing and building strategies to provide relevant individuals with quick access to data that is crucial to making better and more informed business decisions.
- Tracking the behavior of the applications used by a particular business, how they interact with each other and users.
- Matching a business’s strategy with the programs and systems to accomplish the business’s objectives.
What Are the Projects in Data Science Courses?
Data science short courses typically include a project that allows you to implement the skills and knowledge you’ve gained as part of your coursework, allowing you to work through real-world scenarios. This provides opportunities for additional learning and establishes areas that need improvement or skills that need further development.
The scope of the project depends on the focus of the course that you are enrolled in. For example, a course in data cleaning may provide you the opportunity to use the Python data analysis library, known as pandas, to clean up datasets and use exploratory data analysis to translate the data into usable information. A course in communication and interactive data visualizations might include a project consisting of a presentation where data is transformed into images or graphs that allow users to understand the presented data.
Online data science courses may help you obtain valuable skills, whether you’re already working in the field or only just starting out. These programs may give you the flexibility to complete the course requirements in the way you choose, making them an option for those wanting to add to their knowledge and skills while working. Learn more today about how you can further your career with an online master’s in data science program.
Last updated: November 2020