Demand for professionals skilled in data, analytics, and machine learning is exploding. The U.S. Bureau of Labor Statistics reports that demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. Data scientists bring value to organizations across industries because they are able to solve complex challenges with data and drive important decision-making processes. Not only is there a huge demand, but there is a significant shortage of qualified data scientists with 39% of the most rigorous data science positions requiring a degree higher than a bachelor’s.
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Demand for professionals skilled in data, analytics, and machine learning is exploding. The U.S. Bureau of Labor Statistics reports that demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. Data scientists bring value to organizations across industries because they are able to solve complex challenges with data and drive important decision-making processes. Not only is there a huge demand, but there is a significant shortage of qualified data scientists with 39% of the most rigorous data science positions requiring a degree higher than a bachelor’s.
Demand for professionals skilled in data, analytics, and machine learning is exploding. The U.S. Bureau of Labor Statistics reports that demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. Data scientists bring value to organizations across industries because they are able to solve complex challenges with data and drive important decision-making processes. Not only is there a huge demand, but there is a significant shortage of qualified data scientists with 39% of the most rigorous data science positions requiring a degree higher than a bachelor’s.
This MicroMasters program in Statistics and Data Science is comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning. You will dive into the fundamentals of probability and statistics, as well as learn, implement, and experiment with data analysis techniques and machine learning algorithms. This program will prepare you to become an informed and effective practitioner of data science who adds value to an organization. The program certificate can be applied, for admitted students, towards a PhD in Social and Engineering Systems (SES) through the MIT Institute for Data, Systems, and Society (IDSS) or may accelerate your path towards a Master’s degree at other universities around the world.
Anyone can enroll in this MicroMasters program. It is designed for learners that want to acquire sophisticated and rigorous training in data science without leaving their day job but without compromising quality. There is no application process but college-level calculus and comfort with mathematical reasoning and Python programming are highly recommended if you want to excel. All the courses are taught by MIT faculty at a similar pace and level of rigor as an on-campus course at MIT. This program brings MIT’s rigorous, high-quality curricula and hands-on learning approach to learners around the world – at scale.
For more detail on this program and credit pathways, please visit https://micromasters.mit.edu/ds/
What's inside
Three courses
Probability - The Science of Uncertainty and Data
(192 hours)
Probability - The Science of Uncertainty and Data
(192 hours)
Fundamentals of Statistics
(204 hours)
Fundamentals of Statistics
(204 hours)
Machine Learning with Python: from Linear Models to Deep Learning
(180 hours)
Machine Learning with Python: from Linear Models to Deep Learning
(180 hours)Learning objectives
- Master the foundations of data science, statistics, and machine learning
- Analyze big data and make data-driven predictions through probabilistic modeling and statistical inference; identify and deploy appropriate modeling and methodologies in order to extract meaningful information for decision making
- Develop and build machine learning algorithms to extract meaningful information from seemingly unstructured data; learn popular unsupervised learning methods, including clustering methodologies and supervised methods such as deep neural networks
- Finishing this micromasters program will prepare you for job titles such as: data scientist, data analyst, business intelligence analyst, systems analyst, data engineer
- Master the foundations of data science, statistics, and machine learning
- Analyze big data and make data-driven predictions through probabilistic modeling and statistical inference; identify and deploy appropriate modeling and methodologies in order to extract meaningful information for decision making
- Develop and build machine learning algorithms to extract meaningful information from seemingly unstructured data; learn popular unsupervised learning methods, including clustering methodologies and supervised methods such as deep neural networks
- Finishing this micromasters program will prepare you for job titles such as: data scientist, data analyst, business intelligence analyst, systems analyst, data engineer
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