Is Georgia Tech's OMS In Analytics Worth Your Time And Money?
Businesses are increasingly relying on data to help make informed decisions – from product development to marketing to customer service and more. This highly sophisticated, detail-focused, data-driven business environment offers plenty of benefits for individuals who are ready to master data analytics for purposes of solving day-to-day organizational problems. A Georgia Tech OMS in Analytics covers the skills you need to stand out to potential employers and perform with distinction in any data analytics role.
About Georgia Tech University
The Georgia Institute of Technology is a leading research university providing over 20,000 undergraduate and graduate students with courses in analytics. Founded in 1785, and ranked 4th best in the undergraduate engineering programs, Georgia Tech University is the hallmark of America’s higher education. What started as a commitment to inspire the future generations to grow stronger is today a top-value in research and capable of tackling the world’s leading challenges, including creating dependable data platforms to help advance economic growth and foster global security. The institution’s interdisciplinary approach gives you the chance to learn from knowledge experts all over the world. Perhaps this explains why Georgia Tech OMS Analytics acceptance rate is on the rise.
About Earning Your Master’s Degree in Analytics from Georgia Tech University
With the Georgia Tech Master’s Degree in Analytics, you can easily build and strengthen your expertise in decision making and problem solving while making yourself more valuable to a host of different companies worldwide. The institution’s approach gives you the chance to learn from most experts in statistics, operations research, and business intelligence. This course work is ideal for professionals with a STEM background and is interested in knowing how to garner, organize, and analyze data. You will learn to be a systems architect with the knowledge and skills to prepare data for various advanced analytics while focusing on gaining mastery with the right tools used for data governance and analysis.
Why Georgia Tech University Online Master’s Degree in Analytics?
Georgia Tech delivers these online course units to bridge the gap between data science and business management by equipping you with the essential skills and expertise to take your career to a different level. You will gain problem-solving and decision-making skills that happen to be vital in the current business world and end up opening your career path to exciting managerial and consultancy business and annalistic roles.
Perfect for working professionals, this online course from Georgia Tech University allows you to focus on data analysis while leaving prepared to develop insight and sharpen your skills to work across various disciplines to be able to uncover various answers to analytics problems.
To approach any analytic problem, you should develop an extensive set of interdisciplinary tools provided by OMS Analytics. They include:
- Identifying problems
- Finding solutions to problems
- Identifying and tapping into different data streams
- Using various mathematical models to solve problems
- Executing a viable analytics project
Georgia Tech OMS in Analytics Admission Requirements
To apply for this online course, you are required to have:
- One college course or knowledge in probability and statistics and computer programming in Python
- Have a college course in Calculus and linear algebra
- An undergraduate Bachelor’s degree from an accredited institution
If you do not have a background in math or computing, you can still be admitted. In such a case, you will be expected to grasp the necessary basic knowledge before the start of the program. You may also be required to take one preparatory course once you enroll. All applicants chosen for admission will be admitted to this program after passing the OMS Analytics course with an average of B.
You will be relieved to learn that you do not need to take the foundational courses before registering for other elective courses. But it is highly recommended that students take one foundational course in every semester they enroll for until they are admitted.
Georgia Tech’s OMS in Analytics Expected Learning Outcomes
Master of science in analytics is an interdisciplinary program that combines operations research, computing, business, and statistics to equip learners with the ability to solve problems in the tech sector.
By enrolling for this course work, you can tie together the new opportunities it brings through data analysis coupled with computing and advanced quantitative methods from operations research to improve business intelligence and decision support.
As a graduate, you will also be able to move into business and government positions where you can apply the practical knowledge you have garnered to benefit your employers.
Students taking this course will understand and integrate basic fundamental principles and other concepts into the core analytical disciplines of business. Being trained by top-notch faculty in the areas, you can also learn
- Basics of identifying and framing issues
- Acquisition, management, and the utilization of fast-moving streams of information
- Creating solutions and interpreting mathematical models via appropriate methodologies
- Integrating disciplinary skills to help enable you to develop analytical projects
Learning Method
This graduate master’s degree is offered online through the edX online learning platform. The two are designed to help gain access to a flexible and seamless learning experience. By diving into this amazing learning experience, you will utilize the following learning experiences:
- Slide-decks coupled with commentary.
- Discussion forums with flexible office hours
- Practical exercises in data analysis
- Discussion prompts
- Video capture and pre-recorded lessons
- Online quizzes
- Blogs
- Case studies and reviews
It is imperative that you actively participate in the online discussion boards and graded discussion prompts.
OMS in Analytics Course Duration
Based on your learning schedule and flexibility, it will take you 1-3 years to complete this course.
Further reading: Online Learning: How To Get The Most Out Of An Online Course
Georgia Tech Masters Degree in Analytics Course Modules
Course Modules
Introductory– Core
Data Analytics and Modeling
At the end of this introductory module, learners are expected to understand the principles and concepts of data analytics and modeling, including visualization. You will be able to create accurate narratives from complex datasets using computational techniques. Learners will be equipped with the hands-on skills needed to successfully access, identify different structures of databases, and generate reports and summaries for different audiences. Learners will be introduced to state-of-the-art data mining, processing, analysis skills. You will also learn basic programming skills, including multidimensional arrays and programming languages.
Business Management and Data Analytics
This module introduces learners to the correlation between data analytics and business management. You will learn the fundamentals relationship between business management and data analytics. Important basic concepts of business management, including management styles, principles, and functions, and how such correlates with data will be covered in this module. Learning will also cover business language, leadership skills, and how businesses can generate value using data analytics in today’s competitive environment. At the end of this module, you will be expected to understand the importance of business intelligence and how it interlinks with data analytics. This module will be an accelerated introduction to business management aimed at refreshing the learners in previous courses. This module is primarily aimed at fast-tracking the learner’s introduction to the world of data analytics and business intelligence. You will be required to collect and analyze data from case studies or personal experiences to attain learning outcomes.
Databases & Information Management
This module teaches learners important data management skills, including retrieval, organization, analysis, and presentation. During this module, you will learn different data formats and retrieve both basic and complex data from real-world database systems using different models. You will also learn how database management systems work, where learners will be expected to identify and understand the various programming languages used in coding these systems. This introductory module requires basic knowledge in database management and coding.
Advanced – Core
Data Visualization
This module focuses on the quantitative facets of data analytics. During this module, learners will learn how to build different data visualization models using quantitative approaches successfully. In particular, you will be required to access, analyze, and visualize highly complex datasets in different dimensions. Learners will then be required to use such knowledge to build data visualization models to solve real-world problems. You will learn important concepts of data management, such as forecasting, mining, and simulation. This model will also cover other areas, including data optimization and stochastics through theory, practical hands-on learning, and case studies. Aspects of predictive analytics, including nonlinear data relationships, will also be covered under this module. Learners will be expected to acquire skills in situational analysis and decision-making when it comes to which predictive data analysis model would achieve the optimum results.
Programming for Data Analytics
This module equips learners with programming knowledge and skills required to develop their skill base as data scientists. Practical and theoretical skills in programming languages, including Python, will be part of this module. Learners will master data analytics-related programming and apply them in real-world situations.
Statistics – Elective
Machine Learning
This module equips learners with theoretical and practical knowledge and skills on the application of machine learning. Learners will apply machine learning skills and knowledge in real-word situations at the end of this course. This module covers coding for machine learning and techniques.
Regression Analysis
This module teaches the different types and methods of regression. At the end of this module, learners should develop simple research designs and analysis models.
Operations elective
Data Simulation
This module teaches the use of data to create models for problem identification, solving, and forecasting. Learners will have the opportunity for hands-on application of data modeling to solve imagined and real-life problems.
Track electives
Data Analytics for Business Management
This module focuses on the relationship between decision-making and data within the business environment. Learners will get insights on how businesses can transform data into important decision-making tools and setting a firm on a path towards success. This module also equips learners with a multidimensional view of business intelligence and analytics, including mythologies for mining, analyzing, handling, and utilizing business data. Important aspects, such as ethics and challenges in business data consumption, will also be covered.
Practicum
The practicum offers learners and outside companies an excellent opportunity to learn, share ideas and knowledge, and tackle real-life data analytics and business-related problems. The project is specifically designed to help learners identify business problems and help the company find solutions using data analytics or business intelligence as the primary foundation. Learners are expected to explore the full breadth of the module lessons, including data analytics tools and practical leadership skills in problem identification and decision-making during the period of this practicum.
Introduction to Computing for Data Analytics
Computational techniques required for data analysis include programming, gaining access to various databases, basic numerical computing, coupled with visualization. The module is structured to be completed in 12 months and students are trained by the world’s top-notch faculty. You will learn how to frame problems, acquire, manage, and utilize large streams of data.
Why You Should Take These Modules
The modules outlined above are designed to help you with the skills to help various companies deal with data’s ever-increasing complexities. The programs emphasize the application of data science analytics in helping to transform data into viable information that can support decision making.
You will also learn to interpret mathematical models using basic methodologies while integrating the same skills to develop analytics projects. Over and above, computational techniques required for data analysis, such as programming, basic numerical computing, coupled with visualization are skills you are likely to garner from this module.
Skill Information
These modules aim to prepare you to manage, analyze, and interpret heterogeneous data sources. Eventually, you should be capable of designing, comparing, and selecting the appropriate data analytics techniques and measures, using various software tools for data management and storage. You should also be able to help companies that need to deal with large data sets.
How Much Does Georgia Tech’s OMS In Analytics Cost?
This 11 course, fully online Master’s Degree in Analytics costs $9,900
Georgia Tech Masters Degree in Analytics: Final Thoughts
Georgia Tech’s online master of science and data analytics provides world-class instruction not just in statistics and operations research but also in computing and business. OMS Analytics from Georgia Tech provides amazing flexibility for professionals who desire to advance their skills, usually without putting their professional career on hold.
Discover more information about how you can start your journey to a lucrative career in data analytics. An excellent place to start is to check out Georgia Tech’s Online Master’s Degree in Analytics program.
