Data Science for Business | 6 Real-world Case Studies is a training course on solving 6 business problems along with building artificial intelligence models, in-depth learning, and natural language processing for sales, marketing, and HR and PR projects.
Data science is one of the hottest areas of technology right now, full of job opportunities; Today, data science is used in many fields such as banking, healthcare, transportation, and technology. In business organizations, data science is used to optimize business processes, maximize revenue, and reduce costs. The aim of this course is to provide the knowledge needed for key aspects and applications of data science in business in a practical, easy and interesting format.
What is the Data Science for Business course | You will learn 6 Real-world Case Studies:
- Development of an artificial intelligence model to reduce the cost of job search and employee training by predicting the likelihood of people leaving the job
- Development of an in-depth learning model for automating and optimizing the hospital diagnosis process
- Development of time series forecasting models to predict future product prices
- Development of models for defect detection, classification, and positioning
- Optimize marketing strategies by categorizing customers
- Development of natural language processing models to analyze customer feedback on social networks and identify customer intent
Instructors: Dr. Ryan Ahmed, Ph.D., MBA, Mitchell Bouchard, Stemplicity Q&A Support and Agency Team
Number of Courses: 74
Duration: 11 hours and 40 minutes
Course topics on 2021/2:
Prerequisites for Data Science for Business | 6 Real-world Case Studies:
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.
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