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Russ Thomas

Learn to leverage predictive models and methods directly in SQL Server. This course will demonstrate the capabilities of SQL Server related to predictive analytics, including best practices and optimizations.

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Learn to leverage predictive models and methods directly in SQL Server. This course will demonstrate the capabilities of SQL Server related to predictive analytics, including best practices and optimizations.

SQL Server remains one of the most popular data platforms on the planet. Many industries want to leverage popular predictive models using SQL Server and recent features, enhancements, and the power of the cloud have made this more accessible than ever.

In this course, Predictive Analysis with SQL Server, you'll learn how to prepare data for predictive analytics within SQL Server.

First, you'll see some of the most popular methods for predictive models, such as regressions and clustering, demonstrated with hands-on demos and code samples.

Next, you'll dig into analyzing the effectiveness of these queries.

Finally, you'll explore optimizing the SQL Server platform for these types of analytical workloads.

By the end of this course, you'll have the skills and knowledge of building a predictive model directly in SQL Server needed to leverage this platform to perform practical and effective analysis using real-world data.

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What's inside

Syllabus

Course Overview
Preparing SQL Server for Predictive Analytics
Practical Predictive Analytics with SQL Server

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches real-world data analysis using SQL Server
Delves into predictive analytics methods like regression and clustering in SQL Server
Explores practical applications of predictive analytics in data platforms like SQL Server
Facilitates hands-on implementation of predictive models directly in SQL Server
Provides optimization techniques for SQL Server platform to handle predictive analytics workloads
Assumes prior knowledge of SQL Server and data analysis fundamentals

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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 Predictive Analysis with SQL Server with these activities:
Review Types of Predictive Models
By reviewing the types of predictive models, you will gain a stronger foundation for understanding the concepts covered in this course.
Browse courses on Predictive Models
Show steps
  • Revisit regression models, such as linear regression and logistic regression.
  • Review clustering models, such as k-means and hierarchical clustering.
  • Explore decision tree models, such as CART and ID3.
Follow a Tutorial on SQL Server's Predictive Analytics Features
This will provide hands-on experience with the tools and techniques used in predictive analytics with SQL Server.
Show steps
  • Find a tutorial that covers SQL Server's predictive analytics features.
  • Follow the steps in the tutorial to create a predictive model in SQL Server.
  • Test the model on a dataset and evaluate its performance.
Practice Building Predictive Models in SQL Server
Practice is essential for developing proficiency in building predictive models in SQL Server.
Show steps
  • Create a dataset that is suitable for predictive modeling.
  • Try different predictive models and compare their performance.
  • Use SQL Server's built-in functions for data preparation and model building.
  • Evaluate the performance of your models using appropriate metrics.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Study Group for Predictive Analytics
This will provide you with a support system and allow you to learn from others.
Show steps
  • Find a study group that is focused on predictive analytics.
  • Attend the study group meetings regularly.
  • Participate in discussions and share your knowledge.
  • Work together on projects and assignments.
Create a Blog Post on a Predictive Analytics Project
Creating a blog post will help you solidify your understanding of predictive analytics and SQL Server by explaining the concepts to others.
Show steps
  • Choose a predictive analytics project that you have worked on.
  • Describe the problem that you were trying to solve.
  • Explain the data that you used and the models that you built.
  • Discuss the results of your project and what you learned.
Participate in a Predictive Analytics Competition
This will push your skills to the limit and help you learn from others in the field.
Show steps
  • Find a predictive analytics competition that is relevant to your interests.
  • Form a team or work individually on the competition.
  • Use your skills in SQL Server and predictive analytics to solve the problem.
  • Submit your solution and compete for prizes.
Volunteer as a Data Scientist Mentor at a Local Organization
Mentoring others will help you solidify your understanding of predictive analytics and SQL Server by teaching others.
Show steps
  • Find a local organization that provides data science mentorship.
  • Sign up to become a volunteer mentor.
  • Provide guidance and support to aspiring data scientists.
  • Share your knowledge and experience in predictive analytics and SQL Server.

Career center

Learners who complete Predictive Analysis with SQL Server will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use predictive analysis to identify trends, patterns, and relationships in data, helping businesses make better decisions. This course provides a foundation in predictive analytics methods and techniques, enabling you to develop and implement predictive models in SQL Server. As a Data Analyst, you'll play a crucial role in transforming raw data into actionable insights, driving business growth and innovation.
Machine Learning Engineer
Machine Learning Engineers develop and deploy predictive models using advanced algorithms and techniques. This course offers hands-on experience in building predictive models directly in SQL Server, providing you with a solid foundation in the practical application of machine learning principles. By mastering these skills, you'll be well-positioned for a successful career as a Machine Learning Engineer, leveraging SQL Server's capabilities to solve complex business problems.
Data Scientist
Data Scientists combine statistical and programming skills to extract insights from data. This course provides a comprehensive overview of predictive analytics techniques and best practices, enabling you to build and evaluate predictive models in SQL Server. As a Data Scientist, you'll use these skills to uncover hidden patterns, predict future trends, and drive data-driven decision-making.
Business Intelligence Analyst
Business Intelligence Analysts use data to provide insights and recommendations to businesses. This course equips you with the knowledge and skills to leverage predictive analytics in SQL Server, enabling you to identify opportunities, forecast trends, and support informed decision-making. By mastering these techniques, you'll become a valuable asset in any organization, helping businesses stay competitive and make data-driven choices.
Statistician
Statisticians use statistical methods to analyze and interpret data. This course provides a solid foundation in predictive analytics, enabling you to apply statistical techniques to build and evaluate predictive models in SQL Server. As a Statistician, you'll use these skills to uncover insights, make predictions, and inform decision-making in various fields such as healthcare, finance, and market research.
Database Administrator
Database Administrators ensure the availability, performance, and security of databases. This course offers insights into optimizing SQL Server for predictive analytics workloads, enabling you to manage and maintain databases efficiently. As a Database Administrator, you'll play a critical role in ensuring the infrastructure supporting predictive analytics is robust and scalable, meeting the demands of data-driven organizations.
Data Architect
Data Architects design and manage data systems to meet business needs. This course provides a foundation in predictive analytics and SQL Server, enabling you to design and implement data architectures that support predictive modeling. As a Data Architect, you'll leverage these skills to ensure data is structured and accessible for effective analysis, empowering organizations to make data-driven decisions.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course offers insights into building predictive models in SQL Server, providing you with valuable skills for developing data-driven applications. As a Software Engineer, you'll be able to integrate predictive analytics into software solutions, enabling organizations to automate decision-making and improve efficiency.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course provides a foundation in predictive analytics techniques, enabling you to apply them to financial data in SQL Server. As a Quantitative Analyst, you'll use these skills to develop trading strategies, manage risk, and make informed investment decisions, contributing to the success of financial institutions.
Risk Analyst
Risk Analysts identify, assess, and manage risks in organizations. This course offers insights into predictive analytics and SQL Server, enabling you to develop models for risk assessment and mitigation. As a Risk Analyst, you'll use these skills to help organizations make informed decisions, reduce potential losses, and ensure compliance with regulations.
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty in insurance and finance. This course provides a foundation in predictive analytics techniques, enabling you to apply them to actuarial problems in SQL Server. As an Actuary, you'll use these skills to develop pricing models, evaluate insurance risks, and make informed decisions, contributing to the financial stability of organizations.
Market Researcher
Market Researchers analyze market trends and consumer behavior. This course offers insights into predictive analytics and SQL Server, enabling you to develop models for market forecasting and segmentation. As a Market Researcher, you'll use these skills to identify market opportunities, understand customer preferences, and develop effective marketing strategies, driving business growth and innovation.
Epidemiologist
Epidemiologists investigate the causes and patterns of disease in populations. This course provides a foundation in predictive analytics and SQL Server, enabling you to develop models for disease surveillance and outbreak prediction. As an Epidemiologist, you'll use these skills to monitor disease trends, identify risk factors, and develop prevention and control strategies, contributing to public health and safety.
Financial Analyst
Financial Analysts evaluate the financial performance of companies and make investment recommendations. This course offers insights into predictive analytics and SQL Server, enabling you to develop models for financial forecasting and stock analysis. As a Financial Analyst, you'll use these skills to assess investment opportunities, make informed recommendations, and contribute to the success of investment portfolios.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to improve efficiency and decision-making in organizations. This course provides a foundation in predictive analytics and SQL Server, enabling you to develop models for optimization and resource allocation. As an Operations Research Analyst, you'll use these skills to solve complex business problems, reduce costs, and enhance operational performance.

Reading list

We've selected 18 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Predictive Analysis with SQL Server.
Classic textbook on statistical learning. It provides a comprehensive overview of the field, including topics such as supervised learning, unsupervised learning, and model selection. It valuable resource for anyone who wants to learn more about the theory behind machine learning.
Comprehensive textbook on pattern recognition and machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone who wants to learn more about the theory and practice of machine learning.
Provides a practical introduction to data science for business professionals. It covers a wide range of topics, including data mining, machine learning, and data visualization. It valuable resource for anyone who wants to learn more about how to use data to make better business decisions.
Provides a practical guide to building predictive models. It covers a wide range of topics, including data preparation, model building, and model evaluation. It valuable resource for anyone who wants to learn more about how to build predictive models.
Provides a comprehensive overview of machine learning theory and practice. It valuable resource for anyone who wants to learn more about machine learning, even if they are not using SQL Server.
Is helpful for learners who want to explore different toolsets for data mining. It provides a lot of background information on data mining algorithms and techniques, and it covers more advanced topics such as text mining and time series analysis.
Provides a comprehensive overview of data mining techniques using the R programming language. It covers a wide range of topics, including data preparation, data mining algorithms, and model evaluation.
Provides a comprehensive overview of machine learning using the Python programming language. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.
Provides a practical introduction to machine learning using the R programming language. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.
Provides a comprehensive overview of data mining techniques and how they can be applied to business intelligence. It covers a wide range of topics, including data preparation, data mining algorithms, and model evaluation.
Provides a comprehensive overview of machine learning using the TensorFlow framework. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.
Is useful as an introduction to deep learning if learners want to extend their knowledge in this area. It covers many of the same topics as the course textbook, but it goes into more depth about deep learning models.
Provides a gentle introduction to machine learning. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.
Provides a gentle introduction to machine learning. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.
Provides a gentle introduction to machine learning using the Python programming language. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.
Provides a gentle introduction to machine learning. It covers a wide range of topics, including data preparation, machine learning algorithms, and model evaluation.

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