Data Science for Business | 6 Real-world Case Studies
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.
Get a Reminder
| Rating | 4.3★ based on 76 ratings |
|---|---|
| Length | 11.5 total hours |
| Starts | On Demand (Start anytime) |
| Cost | $12 |
| From | Udemy |
| Instructors | Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard, Stemplicity Q&A Support |
| Download Videos | Only via the Udemy mobile app |
| Language | English |
| Subjects | Business |
| Tags | Business Business Analytics & Intelligence |
Get a Reminder
Similar Courses
What people are saying
easy to follow
The lectures are very easy to follow and I do like the practical projects approach.
Learning by doing; structured in such way that it is easy to follow.
Read more
case studies
Great case studies, especially the last one, learned a lot, glad I purchased this course!
While the case studies give insight into how things are done, you will not get any experience as the coding practice involves the instructor going through the motion of pre-written code.
Course seems very interesting and include practical case studies in business .
And last, the case studies are solved just once and we see no improvements are being made even when the accuracy of the models is low.
Read more
real world
This course has issues all over the place - it promises 6 real world case studies but the delivery of learning is poor.
This course is suitable to those who already have the knowledge about data mining/machine learning technique such as python, sklearn, k-means, linear regression, and want to improve the skill of applications to real case in real world.
In real world, we do not stop the work once we receive the accuracy - we continue until the accuracy, precision and recall, everything is acceptable.
Read more
very clear
There is a very clear video missing.
The instructor voice is very clear.
really liked
I really liked the specific case studies, I just don't understand why you recommend this course ('Become a Data Scientist' learning path) before the Machine Learning A-Z course.
I watch Dr Ryan's Youtube Channel and really liked his videos.
Read more
looking forward
looking forward in joining more courses of Dr. Ryan...
Really looking forward to learning more and honing my skills even more.
Read more
dr. ryan
this is such a amazing course and great thanks to Dr. Ryan to conduct this program in an interesting manner.
Dr. Ryan try to explain every important things very clear in a good and simple way!
overall content is good and explanation is good This course is very well done by Dr. Ryan The 6 cases are interesting and each has a real-world application.
Read more
case study
In every case study, you go through a full stack of data mining process, from business perspective, to technology application.
I am on my first case study and I am enjoying the course so far.
Read more
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
AD, Data Science $47k
Associate Data Science Supervisor $55k
Science writer / data analyst $63k
Genomic Data Science Programmer $75k
Volunteer Director of Data Science $78k
Expert Data Science Supervisor $79k
Supervisor 1 Data Science Supervisor $91k
Guest Director of Data Science $101k
Data Science Architect $105k
Head of Data Science $131k
Assistant Director 1 of Data Science $133k
Owner Director of Data Science $149k
Write a review
Your opinion matters. Tell us what you think.
Please login to leave a review
| Rating | 4.3★ based on 76 ratings |
|---|---|
| Length | 11.5 total hours |
| Starts | On Demand (Start anytime) |
| Cost | $12 |
| From | Udemy |
| Instructors | Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard, Stemplicity Q&A Support |
| Download Videos | Only via the Udemy mobile app |
| Language | English |
| Subjects | Business |
| Tags | Business Business Analytics & Intelligence |
Similar Courses
Sorted by relevance
Like this course?
Here's what to do next:
- Save this course for later
- Get more details from the course provider
- Enroll in this course
