| | 21 | -T----- | 11:30A-12:50P | Bauer / 210S | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 5 | 5 | 4 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 22 | -T----- | 11:30A-12:50P | Bauer / 210N | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 0 | 0 | 1 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 23 | -T----- | 1:00P-2:20P | Bauer / 210S | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 0 | 0 | 6 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 24 | -T----- | 1:00P-2:20P | Bauer / 210N | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 0 | 0 | 3 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 25 | --W---- | 10:00A-11:20A | Bauer / 210S | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 5 | 2 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 26 | --W---- | 10:00A-11:20A | Bauer / 210N | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 5 | 1 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 27 | --W---- | 11:30A-12:50P | Bauer / 210S | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 5 | 4 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 28 | --W---- | 11:30A-12:50P | Bauer / 210N | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 35 | 2 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 29 | --W---- | 1:00P-2:20P | Bauer / 210N | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 0 | 0 | 2 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 30 | --W---- | 1:00P-2:20P | Bauer / 210S | Sundaramoorthi | Dec 9 2024 10:00AM - 11:30AM | 35 | 17 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 31 | --W---- | 2:30P-3:50P | Bauer / 210S | Onwujekwe | Dec 9 2024 10:00AM - 11:30AM | 0 | 0 | 2 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 32 | --W---- | 2:30P-3:50P | Bauer / 210N | Onwujekwe | Dec 9 2024 10:00AM - 11:30AM | 5 | 5 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| 33 | --W---- | 4:00P-5:20P | Bauer / 210S | Onwujekwe | Dec 9 2024 10:00AM - 11:30AM | 0 | 0 | 0 | | Desc: | This course will be taught in person. Your final will be on Dec 9, 2024 (Monday) from 10 am to 11:30 am (Central) for all sections. Enrolled students are expected to appear for the exam in-person. Any student approved for remote study will take the exam remotely at the same times listed above. A remote student is expected to have a high-speed internet and webcam-enabled computer. Both your mid-term and final exams will be in the following: BH 130, BH 160, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 109, SH 110, SH 112, SH 113 and SH 122. |
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| | 01 | M-W---- | 11:30A-12:50P | Bauer / 240 | Chib | Dec 16 2024 8:30AM - 11:30AM | 30 | 30 | 13 | | Desc: | Ths course is required for MSFQ students. Your online final will be on Monday, Dec 16 from 8:30 - 11:30 am. |
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| 02 | M-W---- | 1:00P-2:20P | Bauer / 240 | Chib | Dec 16 2024 8:30AM - 11:30AM | 15 | 15 | 18 | | Desc: | This course is required for MSFQ students. Your online final will be on Monday, Dec 16 from 8:30 - 11:30 am. |
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| 03 | M-W---- | 2:30P-3:50P | Bauer / 240 | Chib | Dec 16 2024 8:30AM - 11:30AM | 15 | 15 | 13 | | Desc: | This course is required for MSFQ students. Your online final will be on Monday, Dec 16 from 8:30 - 11:30 am. |
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| 04 | M------ | 6:15P-9:15P | Bauer / 150 | Chib | Dec 16 2024 8:30AM - 11:30AM | 60 | 60 | 12 | | Desc: | Your online final will be on Monday, Dec 16 from 8:30 - 11:30 am.
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| | Description: | Data Visualization has become a core skill set to derive business insights in the data rich business world. Organizations are expecting Business Analysts and Managers to create and disseminate insightful visualizations about the business. This course teaches students the necessary skill set to create insightful visualizations using Tableau to understand patterns prevalent in large datasets which are otherwise difficult to comprehend. In particular, students will learn how to choose and create appropriate visualization based on the following three criteria: 1. Who's the audience looking at the visualization? 2. What is the nature of the business goal (Descriptive, Predictive, or Prescriptive)? 3. What is the data (Categorical, Numerical, Time Series, etc.)? The course will expose students to prevalent business applications of data visualization in different domains (Customer Analytics, Supply Chain Analytics, Healthcare Analytics, Financial Technology Analytics, Accounting Analytics, and Talent Analytics etc.). Upon completing this course, students will know how to create insightful dashboards and other visualizations for different audiences from the given data according to the specified goal. Priority enrollment for all MSA tracks. |
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| | 22 | -T----- | 8:30A-9:50A | Bauer / 210N | Amini | Oct 20 2024 1:00PM - 4:00PM | 5 | 1 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 23 | -T----- | 10:00A-11:20A | Bauer / 210S | Amini | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 1 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 24 | -T----- | 2:30P-3:50P | Bauer / 210S | Amini | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 5 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 25 | -T----- | 2:30P-3:50P | Bauer / 210N | Amini | Oct 20 2024 1:00PM - 4:00PM | 5 | 4 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 26 | -T----- | 4:00P-5:20P | Bauer / 210S | Amini | Oct 20 2024 1:00PM - 4:00PM | 35 | 23 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 27 | -T----- | 4:00P-5:20P | Bauer / 210N | Amini | Oct 20 2024 1:00PM - 4:00PM | 5 | 3 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 28 | ---R--- | 10:00A-11:20A | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 5 | 1 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 29 | ---R--- | 11:30A-12:50P | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 5 | 3 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 30 | ---R--- | 1:00P-2:20P | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 2 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 31 | ---R--- | 2:30P-3:50P | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 32 | ---R--- | 4:00P-5:20P | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 1 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 33 | ----F-- | 10:00A-11:20A | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 1 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 34 | ----F-- | 10:00A-11:20A | Bauer / 210S | Campbell | Oct 20 2024 1:00PM - 4:00PM | 10 | 1 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 35 | ----F-- | 11:30A-12:50P | Bauer / 210S | Campbell | Oct 20 2024 1:00PM - 4:00PM | 0 | 0 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 36 | ----F-- | 11:30A-12:50P | Bauer / 210N | Campbell | Oct 20 2024 1:00PM - 4:00PM | 5 | 0 | 0 | | Desc: | 0our final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| 37 | ----F-- | 1:00P-2:20P | Bauer / 210S | Campbell | Oct 20 2024 1:00PM - 4:00PM | 5 | 5 | 0 | | Desc: | Your final will be on Sunday, Oct 20 from 1:00 - 4:00 pm in one of the following rooms: BH 130, BH 150, BH 160, BH 210, BH 230, BH 240, BH 330, SH 103, SH 105, SH 106, SH 107, SH 108, SH 109, SH 110, SH 112 and SH 122. |
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| | 21 | M------ | 10:00A-11:20A | Bauer / 160 | Amini | Paper/Project/TakeHome | 0 | 0 | 1 | | | |
| 23 | M------ | 1:00P-2:20P | Bauer / 160 | Amini | Paper/Project/TakeHome | 5 | 5 | 1 | | | |
| 24 | M------ | 4:00P-5:20P | Simon / 107 | Amini | Paper/Project/TakeHome | 5 | 5 | 0 | | | |
| 25 | -T----- | 8:30A-9:50A | Simon / 108 | Amini | Paper/Project/TakeHome | 5 | 4 | 0 | | | |
| 26 | -T----- | 10:00A-11:20A | Simon / 108 | Amini | Paper/Project/TakeHome | 0 | 0 | 4 | | | |
| 27 | -T----- | 1:00P-2:20P | Simon / 106 | Amini | Paper/Project/TakeHome | 5 | 5 | 0 | | | |
| 28 | -T----- | 2:30P-3:50P | Simon / 106 | Amini | Paper/Project/TakeHome | 0 | 0 | 5 | | | |
| 29 | --W---- | 10:00A-11:20A | Bauer / 160 | Amini | Paper/Project/TakeHome | 5 | 3 | 0 | | | |
| 30 | --W---- | 11:30A-12:50A | Bauer / 160 | Amini | Paper/Project/TakeHome | 5 | 5 | 0 | | | |
| 31 | --W---- | 1:00P-2:20P | Bauer / 160 | Amini | Paper/Project/TakeHome | 0 | 0 | 0 | | | |
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| | Description: | This MSSCM course provides students the necessary skill set to extract reliable insights from large datasets prevalent in supply chain management. In this course, students will develop basic tools to acquire, clean, and analyze supply chain data, which they will then use to improve decision-making processes. Throughout the course, students will use the Python programming language, which is very effective for data manipulation, reporting, and complex optimization. Topics covered include current multi-source data collection technology used in supply chain management, how to transfor data into analyzable formats, how to generate static and interactive data visulalizations to gain supply chain insights, and predictive analytics in supply chain management - with emphasis on machine learning models for demand forecasting and inventory management optimization. |
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| | 23 | M------ | 10:00A-11:20A | Bauer / 210S | Enayaty Ahangar | Project | 5 | 2 | 0 | | | |
| 29 | M------ | 2:30P-3:50P | Bauer / 210N | Fazel Anvaryazdi | Project | 20 | 1 | 0 | | | |
| 31 | M------ | 4:00P-5:20P | TBA | Fazel Anvaryazdi | Project | 0 | 0 | 0 | | | |
| 34 | --W---- | 10:00A-11:20A | Simon / 241 | Balan | Project | 0 | 0 | 1 | | Desc: | No remote option will be offered for this section. |
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| 35 | --W---- | 11:30A-12:50P | Simon / 241 | Balan | Project | 5 | 1 | 0 | | Desc: | No remote option will be offered for this section. |
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| | Description: | Deep learning has become a core skillset required to solve business problems in the unstructured, data-rich business world. Experts estimate approximately that 90% of the data in organizations is in the form of unstructured datasets, including images, texts, customer reviews, videos, and so on. Organizations would like to use these datasets to improve their business. Moreover, deep learning has a significant advantage over other machine learning algorithms in that it does not require extracting "features" manually prior to applying algorithms. Leading-edge organizations are also expecting business analysts and managers to be familiar with applying deep learning models to solve business problems using unstructured data. This course is recommended but is not required for MS-Business Analytics (MSA) students. It will teach students to build deep learning models for solving business problems using Python libraries (e.g., Keras, Tensorflow). We will cover a range of algorithms from neural networks foundations to convolutional and recurrent network structures; these will be applied in domains such as marketing, customer behavior, and predicting finance risks. Students will better understand the practical use of deep learning with the use of the following five questions: (1) How can unstructured datasets be visualized and analyzed? (2) What are neural networks, and how can they be optimized? (3) What is the deep learning model, and how can it be used in business? (4) Which deep learning structure should be usesd for a given business problem? (5) How can a deep learning model be developed to solve business problems? In summary, the course will expose students to prevalent business applications of deep learning in different domains (e.g., customer analytics, supply chain analytics, healthcare analytics, financial technology analytics, accounting analytics, talent analytics). Upon completing this course, students will know how to build and optimize deep learning models for different business applications. Prerequisites: DAT 500S and DAT 561.
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| | 23 | ----F-- | 10:00A-11:20A | Simon / 103 | Tutun | Project | 35 | 20 | 0 | | Desc: | This course is for MSA students. |
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| 24 | ----F-- | 11:30A-12:50P | Simon / 103 | Tutun | Project | 35 | 25 | 0 | | Desc: | This course is for MSA students. |
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| 25 | ----F-- | 1:00P-2:20P | Simon / 103 | Tutun | Project | 35 | 20 | 0 | | Desc: | This course is for MSA students. |
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| | 01 | M-W---- | 8:30A-9:50A | Simon / 108 | Tutun, Onwujekwe | Project | 35 | 35 | 4 | | | |
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| | Description: | This course combines data, statistical methods, and computation to gain insights and make useful inferences and predictions. This course will take a holistic approach to help you understand the critical elements of data science, from data collection and exploratory data analysis to modeling, evaluation, communication of results, and analysis. You will be discussing case studies, understanding the coding process, and hearing from industry experts to give you a hands-on experience with the data science process. Throughout the course, we will emphasize critical analytical thinking skills, data ethics, and data understanding.
By the end of the course, you will be able to use data and reproducible data science methods to answer questions and guide decision-making with an emphasis on applications for a digitally-enabled world.
The digitally enabled organization enjoys access to a plethora of data created from transactions, internal processes, interactions with customers and suppliers, and monitoring of digital and physical assets. Add to that data from government sources, competitors, and social media. This course provides students the skills to make data-driven decision from these varied sources.
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| | 01 | -T----- | 6:00P-7:30P | Bauer / 330 | Fazel Anvaryazdi | See instructor | 0 | 0 | 0 | | Desc: | Only students admitted to Olin's FLEX MBA program who are studying in person can enroll in this section. |
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| 21 | -T----- | 7:45P-9:15P | Remote / BUS | Vittert | No final | 0 | 0 | 0 | | Desc: | Only students admitted to Olin's FLEX MBA program who are studyng remotely can enroll in this section. |
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| | Description: | This course provides students the necessary skill set to extract reliable insights from large datasets prevalent in supply chain management. In this course, students will develop basic tools to acquire, clean, and analyze supply chain data, which they will then use to improve decision-making processes. Throughout the course, students will use the Python programming language, which is very effective for data manipulation, reporting, and complex optimization. Topics covered include current multi-source data collection technology used in supply chain management, how to transfor data into analyzable formats, how to generate static and interactive data visulalizations to gain supply chain insights, and predictive analytics in supply chain management - with emphasis on machine learning models for demand forecasting and inventory management optimization. Prerequisite: Only OMBA, OSMP and PMBA students can take this course. |
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| | 21 | -T----- | 7:00P-8:30P | Remote / BUS | Lin | See instructor | 0 | 0 | 2 | | Desc: | Only OMBA, OSMP and PMBA students can take this course. |
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| | Description: | Data Visualization has become a core skill set to derive business insights in the data rich business world. Organizations are expecting Business Analysts and Managers to create and disseminate insightful visualizations about the business. This course teaches students the necessary skill set to create insightful visualizations using Tableau to understand patterns prevalent in large datasets which are otherwise difficult to comprehend. In particular, students will learn how to choose and create appropriate visualization based on the following three criteria: 1. Who's the audience looking at the visualization? 2. What is the nature of the business goal (Descriptive, Predictive, or Prescriptive)? 3. What is the data (Categorical, Numerical, Time Series, etc.)? The course will expose students to prevalent business applications of data visualization in different domains (Customer Analytics, Supply Chain Analytics, Healthcare Analytics, Financial Technology Analytics, Accounting Analytics, and Talent Analytics etc.). Upon completing this course, students will know how to create insightful dashboards and other visualizations for different audiences from the given data according to the specified goal. Prerequisite: Only OMBA. Online SMP and PMBA students can take this course. |
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| | 21 | ---R--- | 7:00P-8:30P | Remote / BUS | Lin | Project | 0 | 0 | 7 | | Desc: | Only Olin's Online SMP - MSBA , OMBA and PMBA students can enroll in this course. |
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| | 21 | -T----- | 7:00P-8:30P | Remote / BUS | Mondy | See instructor | 0 | 0 | 4 | | Desc: | Only OMBA and PMBA students can take this course. |
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| | Description: | he course will teach students to learn how to use R for making inferential statistical analysis, and modeling with R. The course will show the basic understanding of R programming. We will cover arithmetic and logical operators, vector operations, data structures, manipulating data, fundamentals of R programming (such as if statements, for loops, building functions, etc.), probability, and inferential statistical analysis. Students will learn R programming practically based on the following five questions: Understand fundamental syntax, control statements and functions in R;
Apply R programming concepts through examples; Prepare the datasets in R for statistics and data analytics; Using R for making inferential statistics;
How to use linear regression and modeling with R. In summary, the course will expose students to prevalent R programming by focusing on fundamentals, statistics, and data analytics. Upon completing this course, students will know how to use R programming. Prerequisite: Only OMBA, OSMP and PMBA students can take this course.
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| | 21 | --W---- | 7:00P-8:30P | Remote / BUS | Tutun | Project | 0 | 0 | 2 | | Desc: | Only OMBA, OSMP and PMBA students can take this course. |
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