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innovate faster for their customers. Popular tools (like Jenkins, spinnaker) will be used for <br />teaching. Other tools may be used as needed. <br />638 Deep Deinnin' wrtN=TensorFlow (1.5 credits) <br />TensorFlow is one of the most in -demand and popular open -source deep learning frameworks <br />available today. The course teaches you applied machine learning skills with TensorFlow so you <br />can build and train powerful models. In this hands-on course, you'll learn the necessary tools to <br />build scalable AI -powered applications with TensorFlow. After finishing this course, you'll be <br />able to apply your new TensorFlow skills to a wide range of problems and projects. This course <br />can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer <br />to achieving the Google TensorFlow Certificate. <br />ft.640 Data Collection,;"aria' Mnitiyariate Analysis (1;S "credits) <br />This course teaches students about the advanced data analytics in the business world. Students <br />will learn the method to gather, clean, analyze and model data to provide insights. Students also <br />learn the foundations for statistical inference, the process of inferring properties of an entire <br />population from those of a subset known as a sample, and various modeling, which allows us to <br />associate how differences in data that describe one phenomenon are related to differences in <br />others, Various modellings are used for assessing profitability, setting prices, identifying <br />anomalies, and generating forecasting. Big data has become more and more common in business. <br />This course also covers how to build a multivariate model with big data. <br />� 20 Advanced Operating Systerfi (3,c'r'edits) <br />This course offers graduate students an in-depth understanding and hands-on experience in <br />modern understanding and hands-on experience in modern operating system design and <br />implementation. Topics include progress, memory, file system, I/0, deadlocks, operating system <br />implementations, modern distributed and network system architectures, communication and <br />synchronization in distributed systems, thread and process scheduling. Projects are required. <br />CSE540 Advanced Data Stf ucffjreand r> lgorithms (3 credits)': <br />This course is designed to teach efficient use of data structures and how to design an algorithm to <br />solve a practical problem, Students will learn the logical relations between data structures <br />associated with the real problem and its physical representation. Topics include algorithms and <br />algorithm efficiency analysis, data organization and the applications. Practical use of the arrays, <br />stacks, queues, single and double linked lists, trees, graphs, and heaps will be covered in depth. <br />The class based data models with OOB design concept will also be introduced. <br />Page 52 of 65 <br />