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MIS undergrad - Fall 2023

To-do list of MIS undergrad - Fall 2023

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To-do list of MIS undergrad - Fall 2023

08/28/2023

Plagiarism - Too many steps

Tools

Information Systems and Databases

Microsoft Access or SQL Server

Data Visualization and Analytics

Tableau

Python : For data analytics and visualization.

R: Another popular language for data analytics.

Cloud Computing

Amazon Web Services (AWS)

Microsoft Azure

Google Cloud Platform (GCP) - Bigquery

Algorithm visualization tools like Visualgo can help in understanding how different algorithms work.

Artificial Intelligence

Python (libraries like TensorFlow, PyTorch): For deep learning and AI.

R Programming - GBM, RF

Blockchain and Cryptocurrencies

Ethereum: As mentioned, for understanding smart contracts and decentralized apps.

Bitcoin Core: For a deeper dive into Bitcoin.

Hyperledger: For enterprise blockchain solutions.

Cyber-security

Wireshark: For network protocol analysis.

Kali Linux: A Linux distribution tailored for ethical hacking.

OWASP ZAP: For finding vulnerabilities in web applications.

Industry-specific tools

Supply Chain: Tools like SAP Integrated Business Planning (IBP). ERP

Data analytics and machine learning continuation

Sessions 5 and 7 focus on Activity: Project goal & process and Team formation. You might consider merging these or provide different project milestones for each session.

Sessions 19 and 20 have the same dates and activities. This seems to be a mistake, so you might want to address this.

For the other TDBs, consider:

DevOps in the context of MIS

Augmented Reality/Virtual Reality (AR/VR) in Business Applications

Ethics in Data and AI

API Management and Integrations

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To-do list

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Task

Due date

Who

Column 5

Coursework Analysis: Look at similar Data Analytics courses to see if there is repetition and find where data analytics and management information systems (MIS) topics are similar in our course.

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Introduction to Data Sources: In the first lecture, introduce students to various data sources, including BigQuery, GitHub, and Kaggle.

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Brief of data source

Tools Learning Plan: Develop a plan for teaching students the following tools throughout the course: Tableau, SQL, Excel, Data cleaning techniques, Data preparation methods.

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Future Outlook: Provide students with insights into potential future opportunities, certificates, and career paths related to the course material.

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Guest Speakers and Coaching: Allocate specific time slots in the course schedule for these guest speaker sessions.

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Initial Warnings: Prepare a warning regarding plagiarism and include it in the course materials.

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Assesment link in brightspace

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Field Trip: New York Times:Organize a field trip to New York Times to explore real-world applications of cybersecurity, disaster recovery, and contingency planning.(During Oct 1st week)

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