Data Science for Business | 6 Real-world Case Studies from Udemy

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.

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Teaches advanced methods in Data Science with a focus on business applications

Taught by instructors who are recognized experts in the field

Uses real-world datasets for practical experience

Covers a wide range of topics relevant to data science in business

Designed for experienced data scientists looking to enhance their skills

May require additional background knowledge in data science

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Science for Business | 6 Real-world Case Studies with these activities:

Seek guidance from experienced data science professionals

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Connect with mentors who can provide valuable insights and support throughout your learning journey.

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Attend industry events or meetups to network with data scientists
Reach out to professionals on LinkedIn or other platforms
Identify potential mentors based on their experience and expertise

Review introductory data science concepts

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Review basic data science concepts to strengthen your foundation before starting the course.

Browse courses on Data Science Fundamentals

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Watch a series of video tutorials on data science fundamentals
Read introductory articles or blog posts on data science concepts

Participate in online discussion forums

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Engage with peers and clarify concepts by participating in online discussions related to the course topics.

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Join online discussion forums dedicated to data science
Ask questions, share insights, and respond to others' discussions

Three other activities

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Practice data manipulation and analysis

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Reinforce your understanding of data manipulation and analysis techniques through hands-on exercises.

Browse courses on Data Manipulation

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Solve coding challenges or practice problems involving data manipulation and analysis
Work through practice datasets to apply data analysis techniques

Develop a machine learning model

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Apply your knowledge of machine learning by building a model to solve a real-world problem.

Browse courses on Machine Learning

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Identify a suitable dataset and problem statement
Choose and implement an appropriate machine learning algorithm
Evaluate and refine your model

Contribute to open-source data science projects

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Gain practical experience in data science and contribute to the community by participating in open-source projects.

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Identify open-source data science projects that align with your interests
Review the documentation and contribute code or other resources
Collaborate with other contributors and learn from their expertise

Career center

Learners who complete Data Science for Business | 6 Real-world Case Studies will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists develop algorithms and statistical models that businesses use to optimize operations, identify trends, and make predictions. Those who take this course may be well suited to data science as it provides hands-on experience using real-world datasets in a variety of business contexts.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers apply machine learning techniques to solve business problems. By providing practical experience with real-world datasets, this course can help students build a solid foundation and enhance their skills in machine learning. The course also covers key aspects of data science applications in business, making it particularly relevant for those interested in business applications of machine learning.

See salaries and explore the career path for Machine Learning Engineer

Business Intelligence Analyst

Business Intelligence Analysts use data analysis to provide insights and recommendations to businesses. This course can help students develop the skills needed to gather, analyze, and interpret data, and communicate findings to stakeholders.

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Data Analyst

Data Analysts collect, clean, and analyze data to help businesses understand their customers, optimize operations, and make informed decisions. The course's emphasis on practical, hands-on experience with real-world datasets can provide valuable skills for data analysts.

See salaries and explore the career path for Data Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to help businesses optimize their operations. The course's coverage of topics such as optimization and forecasting can provide valuable skills for operations research analysts.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. The course's focus on statistical modeling and predictive analytics can provide valuable skills for quantitative analysts.

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Data Visualization Analyst

Data Visualization Analysts create visual representations of data to help businesses communicate complex information effectively. The course's emphasis on practical experience with real-world datasets can provide valuable skills for data visualization analysts.

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Risk Analyst

Risk Analysts assess and manage risks for businesses. The course's coverage of topics such as data analysis and forecasting can provide valuable skills for risk analysts.

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Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. The course's focus on statistical modeling and predictive analytics can provide valuable skills for financial analysts.

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Market Research Analyst

Market Research Analysts conduct research to understand customer needs and preferences. The course's emphasis on practical experience with real-world datasets can provide valuable skills for market research analysts.

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Product Manager

Product Managers oversee the development and launch of new products. The course's coverage of topics such as customer segmentation and market analysis can provide valuable skills for product managers.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products and services. The course's emphasis on customer segmentation and predictive analytics can provide valuable skills for marketing managers.

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Sales Manager

Sales Managers lead and motivate sales teams to achieve sales targets. The course's coverage of topics such as time series forecasting can provide valuable skills for sales managers.

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Business Development Manager

Business Development Managers develop and execute strategies to grow a business's customer base. The course's focus on customer segmentation and predictive analytics can provide valuable skills for business development managers.

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Operations Manager

Operations Managers oversee the day-to-day operations of a business. The course's coverage of topics such as optimization and process improvement can provide valuable skills for operations managers.

See salaries and explore the career path for Operations Manager

Data Science for Business | 6 Real-world Case Studies

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