Data Science for Business | 6 Real-world Case Studies (Udemy.com)
Solve 6 real Business Problems. Build Robust AI, DL and NLP models for Sales, Marketing, Operations, HR and PR projects.
Created by: Prof. Ryan Ahmed, PhD, MBA
Last updated June 2024
What 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.
Course 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.
Instructor Details
- 4.6 Rating
1,764 Reviews
Prof. Ryan Ahmed, PhD, MBA
I'm Dr. Ryan Ahmed, professor, engineer, and founder of Stemplicity, where we help people get past the hype and actually build things with AI, Agentic AI, Cloud, and Data Science.
Over the past 10 years, I've taught 1 million learners across 160 countries — 700,000+ enrolled in my Udemy courses, 260,000+ subscribers on the "Prof. Ryan Ahmed" YouTube channel, and 120,000+ on Coursera. I also run corporate AI training for teams at HSBC, RBC, Discover, and Barclays across the US, Canada, and the UK. I held leadership roles at GM, Samsung, and Stellantis in Canada and the U.S., working on electric and autonomous vehicle technologies.
I hold a MASc, PhD, and MBA from McMaster University. I’m also a licensed Professional Engineer and a Stanford-certified program manager with over 60+ published research papers in AI and battery systems.
But credentials are the least interesting part. Here's what I actually believe: "AI is the biggest opportunity of our lifetime", and most people are sitting it out because they think they need to code or have a PhD. You don't. If you're willing to show up and try, I'll help you get good at this.
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Reviews
By Nnabuike Thaddaeus Eze on 11/26/2024
Taking this course for me has been a real eye opener in the field of ML and DL. It's has exposed me to a new world of endless possibilities in the data-world. the language of the resource person is very clear, and the codes are easy to connect with. So, I strongly recommend it.
By Gargi Singh on 6/30/2024
Overall, it was good but could be improved in a few areas, particularly in section 7. The train.csv file included image names that didn't exist in the train images folder, preventing the completion of the last section. Additionally, some code snippets in section 7 lacked clear explanations; for instance, the use of img[mask == 1, 0] = 255 to add red colour to the image was not intuitively explained during the lecture.
By ANIRUDH HEGDE on 8/31/2023
I really love this course. This was the course I was looking for. Being a fresher you really require such kind of projects which gives u a hands-on -experience. I really would wish to see such kinds of courses more and more. Thanks a lot for sharing such a valuable course. I would highly request you to provide more courses like this. Thanks a lot
By Dion Krisnadi on 4/15/2023
The course is a very good overview of how data science is used in various interesting case studies. It is especially interesting to start every case study with a business understanding. The instructor explains clearly how to do each step. However, a few things can be improved. There is no explanation on the hyperparameters of the model and why the instructor choose the given number. At the final case study, the instructor also does not explain what is res_block. Furthermore, I followed the videos, and somehow got an accuracy much lower than the video, which is confusing since there is no explanation. Maybe the course needs to be updated. Overall, I am satisfied with the course. It was an amazing journey. The course may need some update to make this course perfect.
By Anonymized User on 9/5/2022
The course is well suited for those who literally has some prior knowledge about machine learning, as more and more high concepts are being used. If you are a beginner, then this course is not for you.
By Ramakrishnan on 7/14/2022
This course is Excellent . It teaches a lot of amazing techniques and tricks which by the way is outstanding . Trainer is Clear and Amazing with his tutorial to develop the different ML models that he teaches with real world examples of different use cases . I highly recommand this course to all who are interested in DataScience and Machine Learning along with differentprojects . Dr. Ryan Ahmed has put in lots of hard work in creating this course .
By Sérgio Henrique Nilson Backes on 3/7/2021
The course is very nice with good mood and allows for a fast pace. You must have a previous background on deep learning, TensorFlow in order to better understand the classes. Otherwise, you'll be quite loss about the terms and techniques. In the overall, I really enjoyed this course because it does approach complete real world applications for Machine Learning and Deep Learning. I would definitely indicate this course to people seeking a Data Science career path.
By Anshuman Choudhuri on 2/22/2021
Quite suitable for me, already have decent experience with python, but needed some practical understanding of data science applications in business domain. The instructor is teaching well for those who are familiar with python. taking it step by step. He could tell slightly more about few parameters though for example axis, as they come up. one issue faced was that in hr case altho he demonstrated the models but the quality of models were very bad, he should have showed/mentioned ways to improve. still hoping for clearence if the course structure is asynch.
By Helena Rolle on 8/5/2020
Course was unquestionably interesting and highly recommended for budding Data Scientist. Has all buzz needed to get one to the next level. However, the downfall is that the student is left with mounting unanswered questions. Personally I have an unanswered rate of almost 50%. Given that learning occurs differently for all students, this needs to be accounted for. Q&A should also be accepted and hailed as a learning tool: no question is a dumb one. The provided hype of the benefits of the course and concern for students' learning r was diminished and fall flat because of the high level of non- response and untimely responses to questions.
By Sudharshana Bharathi on 7/22/2020
this is such a amazing course and great thanks to Dr. Ryan to conduct this program in an interesting manner. it's amazing that he explains complex concepts in a succinct manner!!! looking forward in joining more courses of Dr. Ryan...
Quality Score
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Overall Score : 92 / 100

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