Data science allows companies to understand and process enormous amounts of data from various sources and gain insights to improve data-driven decision making. With the growth of data science in business and society, the demand for experts in data, analytics, and machine learning has increased. In numbers, the demand equals a 22 percent job growth by 2030, as reported by the Bureau of Labor Statistics (BLS). Put another way, a lot of opportunities await those who are interested in breaking into data-focused industries. And if you’re one of them, you would not even need to commit four years of your life to school to get relevant skills training.
Cue, the Data Science and Machine Learning program brought to you by the MIT Institute for Data, Systems, and Society (IDSS) and edtech platform Great Learning.
Why Enroll in MIT IDSS’ Data Science and Machine Learning Course?
The MIT Institute for Data, Systems, and Society (IDSS) researches how to use data analysis techniques to address complex challenges and societal concerns. It is dedicated to creating analytical techniques used in multiple fields, including finance, energy systems, urbanization, social networks, and health.
With their industry expertise, MIT IDSS has collaborated with edtech platform Great Learning to offer a 12-week Data Science and Machine Learning program. The program caters to reskilling professionals as well as senior managers with experience in data, applied mathematics, and statistics.
Below are four reasons why you should enroll in the program.
1. Flexible and Accessible Learning
With MIT IDSS’ Data Science and Machine Learning course, you can access lectures from anywhere and at any time. How? The program is online and self-paced, comprising over 30 hours of recorded lectures that you can listen to at your convenience. To top it off, the program only costs $1,900, which makes it much more accessible compared to other online programs.
For additional information on fees and payments, contact the Great Learning admissions team at dsml.mit@mygreatlearning.com
2. Learn from Renowned Experts
The MIT Institute for Data, Systems, and Society (IDSS) has world-renowned faculty, giving you the opportunity to learn from the very best. Coming from leading global organizations, these professionals aim to relay their data science and machine learning expertise to students. After completing the program, you get a certificate of completion from MIT IDSS.
3. Personalized Support to Keep You on Track
Every week of the program, you will receive personalized support and mentorship from data science and machine learning experts. You will also get the chance to share your experiences with peers and hear from students from different backgrounds and regions. Additionally, Great Learning offers students a dedicated program manager for academic and nonacademic inquiries.
4. Learn by Doing
The MIT IDSS’ Data Science and Machine Learning Program allows you to build your understanding by resolving practical case studies and exercises. You will practice what you learn by completing three industry-relevant data science projects and working on over 15 real-world case studies.
MIT IDSS’ Data Science and Machine Learning program allows aspiring data scientists to learn vital data science techniques in only 12 weeks.
Learn more about the program here..MIT IDSS Data Science and Machine Learning Program Curriculum Overview
The MIT IDSS’ Data Science and Machine Learning program consists of eight units spread across 12 weeks. Weeks 3, 7, and 10 of the program serve as learning breaks with conceptional sessions to give you time to recharge before you dive deeper into the program. Here’s a breakdown of what you can expect to learn throughout your training.
- Foundations of data science. The first two weeks of the course focus on exploring Python and statistics for data science. The Python module covers NumPy, Pandas, and data visualization, while the statistics module gives you an idea about descriptive and inferential statistics and how they help make effective decisions.
- Machine learning techniques to analyze unstructured data. Learn about unsupervised learning, one of the key components of machine learning, and get immersed in specific techniques, such as K-means clustering. The last module of this part of the curriculum is dedicated to spectral clustering, components, and embeddings.
- Regression and prediction. Examine traditional and contemporary regression techniques for forecasting and drawing conclusions. This part of the curriculum covers classical linear regression, nonlinear regression and extensions, modern regression with high dimensional data, and the use of modern regression for causal inference.
- Classification and hypothesis testing. Learn the essentials of categorization, hypothesis testing, and anomaly detection, which are essential to scientific inquiry. This complex statistical system adheres to a predetermined set of guidelines that will be clarified and placed in the context of classification.
- Deep learning. Dive into essential deep learning concepts, including image classification, back-propagation, transfer learning, natural language processing (NLP), and speech recognition.
- Recommendation systems. Learn how to examine statistical modeling and algorithms to create a viable recommendation system. Then, get introduced to recommendations and rankings, collaborative filtering, and personalized recommendations.
- Networking and graphical models. Gain a thorough understanding of approaches for examining sizable networks, identifying critical structures within them, and extrapolating missing data from networks. Graphical models are powerful tools for modeling network processes and streamlining statistical calculations.
Key Takeaways
Here are the essential features you should know about the MIT IDSS’ Data Science and Machine Learning course.
- The program was designed by MIT faculty and industry experts in collaboration with the Great Learning edtech platform. By the end of the program, you will receive a certificate of completion from MIT IDSS.
- The program is recommended for professionals with a data science background and expertise.
- Classes are delivered online via recorded lectures and led by MIT instructors. You will also receive personalized support from industry experts to ensure they stay on track with their learning.
- The program costs $1,900 and lasts 12 weeks.
- Aside from lectures, you will also work on projects that mimic real-world client problems to instill practical experience.
There is no time like the present to start your IT career. Dive into data science and machine learning with the MIT IDSS program.
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