Course: Data Mining and Decision Making
duration: 6 hours |
Language: English (US) |
access duration: 90 days |
Details
Data mining and data science are rapidly transforming decision-making business practices. For these activities to be worthwhile, raw data needs to be transformed into insights relevant to your business's goals. In this course, you'll walk through each stage of the data mining pipeline covering all requirements for reaching a conclusive and relevant business decision. This course shows you how to produce clean datasets with valid data to ensure accurate insights for sound business decision-making. Examine the role data sources, systems, and storage play in descriptive analytics. Next, you’ll learn how utilizing data mining effectively may provide a competitive advantage and additional knowledge about the market and competitors. Finally, you explore how predictive analytics could provide insights about the future, empowering businesses to make informed decisions.
Result
After completing this course, you understand how data mining can help in the decision-making process.
Prerequisites
No prerequisites.
Target audience
Data analist
Content
Data Mining and Decision Making
Data Mining and Decision Making: Modern Data Science Lifecycle
- Data mining and data science are rapidly transforming decision-making business practices. For these activities to be worthwhile, raw data needs to be transformed into insights relevant to your business's goals.
- In this course, you'll walk through each stage of the data mining pipeline covering all requirements for reaching a conclusive and relevant business decision.
- You'll examine data preparation, descriptive and predictive analytics, and predictive modeling. You'll also investigate the role of model validation and implementation in machine learning.
- On completion, you'll have a solid grasp of how data-driven decision-making has helped other businesses succeed and how it can help yours, too, if you employ the right methods.
Data Mining and Decision Making: Data Preparation & Predictive Analytics
Data preparation transforms raw data into datasets with stable
- structures suitable for predictive analytics. This course shows you
- how to produce clean datasets with valid data to ensure accurate
- insights for sound business decision-making. Examine the role data
- sources, systems, and storage play in descriptive analytics.
- Explore best practices used for data preparation, including data
- collection, validation, and cleaning. Additionally, investigate
- some more advanced data exploration and visualization techniques,
- including the use of different chart types, summary statistics, and
- feature engineering. Upon completing this course, you'll know how
- to gather, store, and analyze data to make reliable predictions and
- smart business decisions.
Data Mining and Decision Making: Data Mining for Answering Business Questions
The data mining process provides the opportunity for businesses
- to collect additional information and insights that are unavailable
- through other everyday operations of the company. Use this course
- to learn more about how utilizing data mining effectively may
- provide a competitive advantage and additional knowledge about the
- market and competitors. Start by examining the essential concepts
- in data exploration using summary statistics and visuals and
- discover different data mining techniques. This course will also
- help you develop an understanding of the complete data mining
- process - data gathering, cleaning, exploration, and mining. After
- completing this course, you'll be able to use data mining to answer
- in-depth questions about any business.
Data Mining and Decision Making: Predictive Analytics for Business Strategies
Predictive analytics enable modern businesses to obtain
- important insights about the market and gaining a competitive
- advantage. Use this course to explore how predictive analytics
- could provide insights about the future, empowering businesses to
- make informed decisions. Start by delving deeper into the concepts
- of deep learning, machine learning, and data. You'll then examine
- neural networks theory of operation and discover natural language
- processing (NLP) and computer vision applications. You'll wrap up
- the course by developing a deeper understanding of the future of
- analytics. Once you've completed this course, you'll be able to
- identify how regression, classification, time-series analysis, and
- recommender engines can be used to drive business decisions. You'll
- also have a solid grasp of using machine learning and deep learning
- methodologies for predictive analytics.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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