Applied Data Science – Practical Training for Business Analytics
Learn how to acquire, manage and present data within a range of organizational settings. Explore and apply techniques for data visualization, predictive modeling, and machine learning.
This data science course introduces you to advanced business analytics topics, linking data models to strategy and decision making. You will learn to use both spreadsheet modeling and statistical programming, and case studies help you apply advanced concepts to practical business problems.
Course Outline
Learn the skills and techniques for data analysis and data-driven decision-making, in a hands-on, collaborative environment with mentors from industry leaders. You will gain an understanding of how to effectively manage, analyze, present and communicate complex information through a clear procedural framework.
BU MET’s Applied Data Science program is a graduate-level curriculum that immerses you in the latest industry tools and approaches within an academically rigorous framework. It focuses on learning to acquire, process, and analyze large datasets for a wide range of organizational contexts, including business, scientific research, security, social impact, and policy.
Through a series of end-to-end data science projects, you will develop the wrangling, analysis, and model-building skills needed for a successful career in the field. You will also build your communication skills, so you can clearly explain the meaning and implications of data-driven decisions to a non-data science audience. You will work with open source Python libraries to import, clean, and manipulate data from a variety of sources.
Course Content
Whether it’s optimizing hospital care or improving corporate marketing strategy, transforming data into knowledge is a crucial skill for professionals across industries. The graduate certificate in applied data science combines foundational coursework with practical, industry-based projects to help you become proficient in data analytics.
The program focuses on using the powerful tools of computer science and statistical methods to turn data into useful information that helps inform decisions and solve real-world problems. You’ll learn to import, clean and wrangle data; analyze it using machine learning models; and create meaningful data visualizations.
You’ll work in a dynamic learning environment that allows you to receive real-time feedback from your instructor, collaborate with other students and attend live sessions. You will also get hands-on experience with a variety of open source libraries in Python, such as scipy and scikit-learn, to build machine learning regression models and predict future trends from data. These skills will prepare you to apply data science techniques in professional, applied research or social impact settings.
Instructors
Whether it’s the medical results of an operation, institutional knowledge in the form of a library database, or consumer buying habits, organizations rely on data for decision-making. As a leader in this field, you can be their lifeline, channeling information into actionable knowledge and adding value to the organization.
With foundational coursework in data mining and machine learning, predictive modeling and analytics, SQL and relational databases, statistical programming in R and Python, and data visualization, you will have the tools to analyze big and unstructured datasets to identify new ways to inform decision-making in your professional or academic domain. The program is designed for professionals and scholars from all fields who want to become conscientious consumers of data and learn to use data-driven techniques to address their own specific challenges.
You can choose from our generalist track, which prepares students to be well-rounded and collaborative members of data science teams, or our specialist track, which builds on your existing skills to prepare you for more technical roles within this field. Both tracks are taught by MIT faculty and mentors who bring real-world expertise from their work in the field.
Course Materials
The course provides you with the opportunity to develop your skills in Data Science using real-world data and projects. You will learn how to collect and import data, clean it, wrangle it, perform exploratory data analysis and create meaningful data visualizations. You will also learn how to predict future trends from data by building linear, multiple and polynomial regression models and creating data pipelines.
This course also teaches you how to communicate your results through data reports and interactive dashboards, which are critical communication tools in the field of business analytics. You will use open source Python graphing libraries such as Matplotlib, Seaborn and Folium to visualize your results.
You will be paired with a mentor who will help you understand best practices and deliver the actionable know-how you need to apply this new skill to your work. Your mentor will work with you every weekend and provide one-on-one guidance to guide your learning and growth in the program.
