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Data Science for Business | 6 Real-world Case Studies

Solve 6 real Business Problems. Build Robust AI, DL and NLP models for Sales, Marketing, Operations, HR and PR projects.
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Platform: Udemy
Video: 11h 40m
Language: English
Next start: On Demand

Table of contents

Description

Are you looking to land a top-paying job in Data Science?
Or are you a seasoned AI practitioner who want to take your career to the next level?
Or are you an aspiring entrepreneur who wants to maximize business revenue with Data Science and Artificial Intelligence?

If the answer is yes to any of these questions, then this course is for you!
Data Science is one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Data Science is widely adopted in many sectors nowadays such as banking, healthcare, transportation and technology.
In business, Data Science is applied to optimize business processes, maximize revenue and reduce cost. The purpose of this course is to provide you with knowledge of key aspects of data science applications in business in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets.
In this course, we will assume that you are an experienced data scientist who have been recently as a data science consultant to several clients. You have been tasked to apply data science techniques to the following 6 departments: (1) Human Resources, (2) Marketing, (3) Sales, (4) Operations, (5) Public Relations, (6) Production/Maintenance. Your will be provided with datasets from all these departments and you will be asked to achieve the following tasks:
•Task #1 @Human Resources Department: Develop an AI model to Reduce hiring and training costs of employees by predicting which employees might leave the company.
•Task #2 @Marketing Department: Optimize marketing strategy by performing customer segmentation
•Task #3 @Sales Department: Develop time series forecasting models to predict future product prices.
•Task #4 @Operations Department: Develop Deep Learning model to automate and optimize the disease detection processes at a hospital.
•Task #5 @Public Relations Department: Develop Natural Language Processing Models to analyze customer reviews on social media and identify customers sentiment.
•Task #6 @Production/Maintenance Departments: Develop defect detection, classification and localization models.

You will learn

✓ Develop an AI model to Reduce hiring and training costs of employees by predicting which employees might leave the company.
✓ Develop Deep Learning model to automate and optimize the disease detection processes at a hospital.
✓ Develop time series forecasting models to predict future product prices.
✓ Develop defect detection, classification and localization models.
✓ Optimize marketing strategy by performing customer segmentation
✓ Develop Natural Language Processing Models to analyze customer reviews on social media and identify customers sentiment.

Requirements

• Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to anyone with basic programming knowledge. Students who enroll in this course will master data science fundamentals and directly apply these skills to solve real world challenging business problems.

This course is for

• Seasoned consultants wanting to transform businesses by leveraging data science and AI.
• Visionary business owners who want to harness the power of Data science and AI to maximize revenue, reduce costs and optimize their business.
• Data Science Practitioners wanting to advance their careers and build their portfolio.
• Tech enthusiasts who are passionate about Data science and AI and want to gain real-world practical experience.
Professor & Best-selling Instructor, 250K+ students
Ryan Ahmed is a best-selling Udemy instructor who is passionate about education and technology. Ryan’s mission is to make quality education accessible and affordable to everyone. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business. 
Ryan held several engineering positions at Fortune 500 companies globally such as Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. Ryan has taught several courses on Science, Technology, Engineering and Mathematics to over 280,000+ students globally. He has over 25 published journal and conference research papers on state estimation, AI, Machine learning, battery modeling and EV controls. He is the co-recipient of the best paper award at the IEEE Transportation Electrification Conference and Expo (iTEC 2012) in Detroit, MI, USA. 
Ryan is a Stanford Certified Project Manager (SCPM), certified Professional Engineer (P.Eng.) in Ontario, a member of the Society of Automotive Engineers (SAE), and a member of the Institute of Electrical and Electronics Engineers (IEEE). He is also the program Co-Chair at the 2017 IEEE Transportation and Electrification Conference (iTEC’17) in Chicago, IL, USA.
* McMaster University is one of only four Canadian universities consistently ranked in the top 100 in the world.


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Platform: Udemy
Video: 11h 40m
Language: English
Next start: On Demand

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