DATA MODELING
DATA MODELING ONLINE
- M 6:10 p.m.-8 p.m.
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Instructor:
Steven Hoberman
Info - 3 points
APPLIED ANALYTICS FRAMEWORKS & METHDS II
APP AN FRAMEWORKS & METHODS II
- R 8:10 p.m.-10 p.m.
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Instructor:
David Shilane
Info - 3 points
APPLIED ANALYTICS FRAMEWORKS & METHDS II
APAN FRMWRKS & MTHDS II ONLINE
- T 6:10 p.m.-8 p.m.
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Instructor:
Gurgen Hayrapetyan
Info - 3 points
PYTHON FOR DATA ANALYSIS
- S 12:10 p.m.-2 p.m.
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Instructor:
Helga Hartelt Baez
Info - 3 points
PYTHON FOR DATA ANALYSIS
PYTHON FOR DATA ANALYSIS ONLNE
- T 8:10 p.m.-10 p.m.
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Instructor:
Max Vilenchik
Info - 3 points
RESEARCH DESIGN
RESEARCH DESIGN ONLINE
- W 8:10 p.m.-10 p.m.
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Instructor:
David Shilane
Info - 3 points
SQL
SQL & RELATIONAL DB ONLINE
- W 8:10 p.m.-10 p.m.
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Instructor:
Nikolaos Machairas
Info - 3 points
MACHINE LEARNING: CONCEPTS & APPLICATION
- T 6:10 p.m.-8 p.m.
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Instructor:
Adrian Heilbut
h-index: 13 Info - 3 points
MANAGING DATA
MANAGING DATA ONLINE
- W 6:10 p.m.-8 p.m.
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Instructor:
Mohamed Mneimneh
Info - 3 points
APPLIED TEXT AND NATURAL LANGUAGE ANALYT
APPLD TXT & NAT LANG AN ONLINE
- M 8:10 p.m.-10 p.m.
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Instructor:
Javid B Huseynov
Info - 3 points
CLOUD COMPUTING
Data analytics have become an essential component of business intelligence and informed decision making. Sophisticated statistical and algorithmic methodologies, generally known as data science, are now of predominant interest and focus. Yet, the underlying cloud computing platform is fundamental to the enablement of data management and analytics.
This course introduces students to cloud computing concepts and practices ranging from infrastructure and administration to services and applications. The course is primarily focused on the development of practical skills in utilizing cloud services to build distributed and scalable analytics applications. Students will have hands-on exposure to VMs (Virtual Machines), databases, storage, microservices, and AI/ML (Artificial Intelligence and Machine Learning) services through Google Cloud Platform, et al. Cost and performance characteristics of alternative approaches will also be studied. Topics include: overview of cloud computing, cloud systems, parallel processing in the cloud, distributed storage systems, virtualization, security in the cloud, and multicore operating systems. Throughout, students will study state-of-the-art solutions for cloud computing developed by Google, Amazon, Microsoft, and IBM.
The course modules provide a blend of lecture and reading materials along with class exercises and programming assignments. While extensive programming experience is not required, students taking the course are expected to possess basic Python 3 programming skills.
The desired outcome of the course is the student’s ability to put conceptual knowledge to practical use. Whether you are taking this course for future academic research, for work in industry, or for an innovative startup idea, this course should help you master the fundamentals of cloud computing.
- W 8:10 p.m.-10 p.m.
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Instructor:
Javid B Huseynov
Info - 3 points
STRATEGY AND ANALYTICS
STRATEGY AND ANALYTICS ONLINE
n/a
- M 6:10 p.m.-8 p.m.
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Instructor:
Mani Vannan
Info - 3 points
ANALYTICS & LEADING CHANGE
ANALYTICS & LEADING CHNG
- S 10:10 a.m.-noon
- F 12:10 p.m.-2 p.m.
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Instructor:
Paul J Bailo
Info -
Instructor:
Anjana Bhattacharyya
Info - 3 points
ANALYTICS & LEADING CHANGE
ANALYTICS & LEADNG CHNG ONLINE
- M 6:10 p.m.-8 p.m.
- W 8:10 p.m.-10 p.m.
- T 6:10 p.m.-8 p.m.
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Instructor:
David Kreutter
Info -
Instructor:
Zachary Kornhauser
Info -
Instructor:
Paula Darling
Info - 3 points
Internship In APAN
This course requires you to experience firsthand a program-related job in a real working environment. You will engage in personal, environmental and organizational reflection. The ideal Internship will provide you an opportunity to gain tangible and practical knowledge in your chosen field by taking on a position that is closely aligned with your coursework and professional interests. Before registering for this course, you must have completed the Internship Application Form in which you will describe your internship sponsor and provide details about the work that you will be doing. This form must be signed by your internship supervisor and approved by your program director BEFORE you register for this course.
To receive instructor approval, the internship:
● Must provide an opportunity for the student to apply course concepts, either at the organizational or team level
● Must fit into the planned future program-related career path of the student
You must identify your own internship opportunities. The internship must involve a commitment to completing a minimum of 210 hours over the semester.
At the end of your course, you will submit an evaluation form to your internship supervisor. The evaluation form should be returned directly to the instructor
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Instructor:
David Slotnick
Info -
Instructor:
Taylor Wordsman
Info - 3 points