Transform the entire business value using the most effective technique: prescriptive analysis. When billions of data are available for companies, it takes more work to examine the collected data. The best way to analyze the collected data is prescriptive analysis, which not only helps businesses identify crucial points but also makes data-driven strategic decisions.
Learn prescriptive analysis and how it works to improve your business performance, limit risk, create loyal customers, and achieve business goals with the best prescriptive analysis courses.
Why is it essential to learn prescriptive analysis?
Prescriptive analysis is like data analytics, which involves tools and processes to collect and analyze the data to get quick suggestions for improving best practices. The most compelling argument favoring prescriptive analytics is that it enables businesses to reflect on previous success and define possible next steps. This is especially important for struggling organizations seeking a turnaround, those with poor performance data, and fledgling companies with only a few years of experience. Prescriptive analytics not only helps determine the best course of action, but it may also estimate the time frame required to reach specified goals.
The prescriptive analytics market will grow at a CAGR of 24% between 2024 -2029. Companies are spending on marketing advertising and changing the customer intelligence landscape to attract loyal customers and speed the market growth. According to the US Bureau of Labor Statistics (BLS), the number of job opportunities for analysts is predicted to grow by 23 per cent between 2022 and 2032, much greater than the five per cent average job growth projected for all jobs in the country.
Does this analytical technique interest you? If so, it’s time to look at the list of the best prescriptive courses online in 2024.
Table of Content
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Best Prescriptive Analytics Courses, Certification, Tutorials, Training, Classes Online
Prescriptive Analytics for Decision Makers [Udemy]
Build the predictive and prescriptive models to analyze the data. This prescriptive analytics course covers the basic application of this type of data analytics for analyzing raw data. You will learn to use this technology to prevent fraud, meet business goals, and create more loyal customers.
Course Instructor
The Udemy Predictive and Prescriptive Analytics Course was created by the Institute of Product Leadership (IPL). This institute has helped many professionals transform their careers to the next level with its programs. This program will be taught by eminent leaders of the product industry who want to share their valuable experience with others.
Pros & Cons
Pros
- Good presentation
- Easy-to-digest content
- Very informative
Cons
- No resources to download
- No hands-on exercises
Key Highlights & Learning Objectives
- The Udemy prescriptive analytics online tutorial is divided into seven chapters, each 5 hours long. Each chapter consists of a set of lectures that are longer than 3 minutes.
- Learn the difference between Cross-sectional and Longitudinal data.
- Understand how to differentiate between a prediction and forecasting problem scenario and how to use these to make data-driven decisions.
- Discover the two types of modelling approaches—parametric and nonparametric—and how to use them to find the critical tradeoff between predictive accuracy and explainability of models.
- Using LPP (linear programming problems), build multiple “What if “scenarios that can inform business decisions.
- Learn about the Gradient Descent Algorithm and its fundamentals.
Who is it for?
This course on predictive and prescriptive analytics is for professionals like engineers, consultants, and business analysts. You must have a prior understanding of data analytics. After completing the course, you can build your own prescriptive analytics model for making data-driven decisions for the business and earn a certificate to upgrade your career.
Rating: 3.6/5
Students Enrolled: 2920
Duration: 5 hours
Customer and Prescriptive Analytics [Coursera]
Prepare to broaden your knowledge with the customer analytics training. It is intended to assist users through all critical components of customer analytics, including descriptive, predictive, and prescriptive analytics. You will learn how these technological components are implemented in real-world businesses such as Amazon, Google, and Starbucks.
Course Instructor
Eric Bradlow, Peter Fader, Raghu Iyenar, and Ron Berman will teach the Customer Analytics Coursera Certification. All four teachers are faculty members at the University of Pennsylvania.
What will you learn
The Coursera consumer analytics course provides an overview of analytics in five fundamental topics, allowing you to make more informed business decisions.
- Introduction: The first lesson covers consumer analytics and gives you a quick overview of what you’ll learn in this organized course.
- Descriptive Analysis: This lesson will start by explaining what data can be used to describe consumer behaviour and the distinction between data describing casual relationships and data describing correlations.
- Predictive Analytics: In this session, you will learn about tools for anticipating customer behaviour and test them to see which ones are appropriate for decision-making.
- Prescriptive Analytics: This fourth lesson will teach you to ask the proper questions, create objectives, and optimize for success.
- Case Studies: The last module will present case studies of successful firms and how they used data to create customer-focused marketing strategies. You’ll also get hands-on experience with real-world five-pronged attacks and how to employ them in customer analytics marketing.
Pros & Cons
Pros
- Excellent introduction and explanation.
- Easy to understand.
- Comprehensive overview.
- Well-structured with excellent examples.
Cons
- Need to be updated
- Not challenging assignments
Key Highlights & Learning Objectives
- Learn the most common strategies for collecting consumer data for organizations and how to use the data to make informed business decisions.
- Develop a thorough understanding of the primary tools used to forecast client behaviour.
- Learn the fundamentals of customer analytics and how to communicate or apply them to make better business decisions.
- Explain the history and current practices of customer analytics in prominent firms.
- Access 40+ videos, 8+ reading materials, and 5+ quizzes to expand your understanding.
Who is it for?
The online customer analytics course is ideal for beginners learning about customer analysis and business optimization approaches. However, it is not intended to prepare students to apply consumer analytics. After finishing the course, you will be equipped to use data for your firm and receive a shareable credential to advance your career.
Rating: 4.6/5
Students Enrolled: 334,492
Duration: 11 hours
Advanced-Data Analytics with Prescriptive Modeling [Coursera]
This business data analytics specialization offers the ultimate solution to growing your business and generating more profits. As a learner, you will explore how business analytics are used to extract and manipulate data.
Course Instructor
Manuel Laguna, Dan Zhang, and David Torgerson instructed this advanced business analytics certification program from the University of Colorado Boulder. These instructors have a lot of experience in their pocket, which makes them share their knowledge related to business analytics, AI, and more with aspirants and professionals.
What you’ll learn
The Coursera Business Analytics Specialization is designed to gain real-world business analytics skills in 5 informative courses.
- Introduction to Data Analytics for Business: This course will describe the information cycle from events and how to identify the types of events involved in business analytics.
- Predictive Modeling: This course will teach you to apply exploratory data analysis to drive insights. Whatever data you’ve prepared will be used for predictive modelling and for finding graphs to explore and display datasets.
- Business Analytics: This course explains how to implement optimization to identify solutions for complex business problems and test these techniques and their feasibility.
- Communicating Business Analytics Results: In this course, you will learn how to identify problems with presenting analytics and discover the strengths and weaknesses of various communication methods for explaining analytics to non-technical stakeholders.
- Capstone Project: In this course, you will get a hands-on project of creating a compelling presentation to share impactful insights. Also, you will learn to design prescriptive analytics models.
Pros & Cons
Pros
- Well-structured and detailed
- Expert-led courses
- Hands-on projects
Cons
- Need practical skills and programming experience
Key Highlights & Learning Objectives
- Learn to apply business data analytics to business problems.
- Understand the entire business analytics process, from collecting, extracting, analyzing, modelling, and presenting findings.
- Gain deep knowledge of SQL commands and use them to extract and manipulate data stored in large databases.
- Learn how to find and apply statistical models for implementing descriptive analytics.
- Able to use prescriptive analytics and predictive analytics tools to set data and interpret results.
- Learn how to use an Excel tool like the Analytic Solver Platform (ASP) to develop models about linear programming and simulation optimization methods.
Who is it for?
TWhether you’re a decision maker, data analyst, or any professional from statistics, you must enrol in this business analytics certification to gain real-world business analytical skills. While walking through each lesson, you must be familiar with Excel and high-level programming. Once you finish all courses and projects, you will become an expert in business analysis to leverage data to solve all complex business problems.
Rating: 4.4/5
Students Enrolled: 99,013
Duration: 1 month, 10 hours/week
FAQ
What are the skills required to learn prescriptive analytics?
Prescriptive analytics is a type of data analytics that not only predicts future outcomes but also suggests actions to achieve desired outcomes. To learn prescriptive analytics effectively, one needs a combination of skills spanning across several domains:
Mathematics and Statistics:
Understanding of probability and statistics.
Knowledge of optimization techniques (e.g., linear programming, nonlinear programming).
Familiarity with decision theory and utility theory.
Data Analysis and Modeling:
Skills in data cleaning, transformation, and preparation.
Ability to create and interpret statistical models.
Experience with machine learning algorithms and predictive modeling.
Programming:
Proficiency in programming languages commonly used in data analytics such as Python, R, or Julia.
Experience with libraries and frameworks for data analysis (e.g., pandas, NumPy, scikit-learn in Python).
Operations Research:
Knowledge of operations research methods, including simulation, stochastic modeling, and heuristics.
Understanding of how to formulate and solve optimization problems.
Business Acumen:
Ability to understand business processes and objectives.
Skills to translate analytical results into actionable business strategies.
Understanding of industry-specific challenges and opportunities.
Data Visualization:
Proficiency with data visualization tools like Tableau, Power BI, or D3.js.
Ability to create clear and effective visualizations to communicate insights.
Database Management:
Knowledge of SQL and experience with database management systems.
Understanding of data warehousing and data mining techniques.
Software and Tools:
Familiarity with prescriptive analytics software like IBM ILOG CPLEX Optimization Studio, Gurobi, or SAS OR.
Experience with integrated development environments (IDEs) and version control systems like Git.
Soft Skills:
Strong problem-solving and critical thinking skills.
Effective communication skills to convey complex analytical concepts to non-technical stakeholders.
Project management skills to handle multiple tasks and deadlines efficiently.
Learning and Adaptation:
Willingness to stay updated with the latest trends and advancements in analytics and technology.
Ability to learn new tools and techniques as they emerge in the field.
Combining these skills will provide a strong foundation to understand and apply prescriptive analytics effectively in various contexts.
Why is the future of data analytics prescriptive analytics?
The future of data analytics is often seen as prescriptive analytics due to several compelling reasons:
Actionable Insights:
Prescriptive analytics goes beyond merely understanding what has happened (descriptive analytics) and predicting what might happen (predictive analytics).
It provides specific recommendations on actions to take to achieve desired outcomes, making the insights directly actionable.
Optimization of Decision-Making:
In an increasingly complex business environment, organizations need to make optimal decisions quickly. Prescriptive analytics helps in identifying the best possible actions by evaluating multiple scenarios and their outcomes, thus enhancing decision-making efficiency and effectiveness.
Integration of Advanced Technologies:
The advancements in artificial intelligence (AI), machine learning (ML), and big data technologies are making prescriptive analytics more accessible and powerful. These technologies enable the handling of large and complex datasets, real-time processing, and the generation of sophisticated recommendations.
Competitive Advantage:
Companies that adopt prescriptive analytics can gain a significant competitive edge. By optimizing their operations, supply chains, marketing strategies, and other business functions, they can increase efficiency, reduce costs, and improve customer satisfaction.
Proactive Approach:
Prescriptive analytics allows organizations to be proactive rather than reactive. Instead of just responding to past trends or future predictions, businesses can anticipate challenges and opportunities and take preemptive actions to address them.
Customization and Personalization:
In fields like marketing, customer service, and healthcare, prescriptive analytics can tailor recommendations to individual preferences and needs. This level of personalization enhances customer experiences and satisfaction.
Resource Allocation:
It aids in optimal resource allocation by identifying the most efficient ways to deploy assets, labor, and capital. This is crucial in sectors like manufacturing, logistics, and healthcare where resources are often limited.
Complex Problem Solving:
Many industries face complex problems that require sophisticated solutions. Prescriptive analytics can model intricate systems and provide solutions that consider multiple variables and constraints, which is often beyond the capacity of traditional analytics methods.
Scalability:
Modern prescriptive analytics solutions are scalable, meaning they can be applied to small-scale operations as well as large, global enterprises. This scalability ensures that businesses of all sizes can benefit from advanced analytics.
Regulatory Compliance:
In sectors such as finance and healthcare, where regulatory compliance is crucial, prescriptive analytics can help ensure that organizations remain compliant by providing recommendations that adhere to regulations and standards.
Enhanced ROI:
By enabling more accurate and efficient decision-making, prescriptive analytics can lead to better financial performance and a higher return on investment (ROI) for analytics initiatives.
In summary, the future of data analytics is geared towards prescriptive analytics because it provides a comprehensive approach to understanding data, predicting outcomes, and most importantly, recommending actions that optimize results.
This ability to directly influence and improve business outcomes makes prescriptive analytics a valuable tool for organizations looking to thrive in a data-driven world.
Conclusion
Becoming a pro in prescriptive analytics allows you to stay ahead of the competition in your current organization. Whether upgrading your career or solving your business problems, learning prescriptive analytics is beneficial. With prescriptive analytics, you can transform raw data into strategic insights to make informed decisions and obtain desired outcomes. From the list, pick the best prescriptive course that meets your goals and decision-making capacity.
