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Algorithms
Sebastian Thrun
and
Josh Bernhard
Sebastian Thrun
and
Josh Bernhard
The algorithms course offers a detailed introduction to fundamental statistical and machine learning algorithms, particularly focusing on regression techniques. The course begins with simple linear regression and progresses to multiple linear regression,...
Read more
The algorithms course offers a detailed introduction to fundamental statistical and machine learning algorithms, particularly focusing on regression techniques. The course begins with simple linear regression and progresses to multiple linear regression,...
Read more
The algorithms course offers a detailed introduction to fundamental statistical and machine learning algorithms, particularly focusing on regression techniques. The course begins with simple linear regression and progresses to multiple linear regression, equipping students with the ability to analyze relationships between multiple variables. Finally, it covers logistic regression, a powerful tool for classification problems.
Register for this course and see more details by visiting:
OpenCourser.com/course/8mzl86/algorithm
What's inside
Syllabus
In this lesson, we kick off the course with an introduction to machine learning and why linear regression is such an important algorithm.
In this lesson, you'll use Python to fit linear regression models, as well as understand how to interpret the results of linear models.
Read more
Syllabus
In this lesson, we kick off the course with an introduction to machine learning and why linear regression is such an important algorithm.
In this lesson, you'll use Python to fit linear regression models, as well as understand how to interpret the results of linear models.
Read more
In this lesson, you'll learn to apply multiple linear regression models in Python. Then you'll learn how to interpret the results and understand if your model fits well.
In this lesson, you'll learn to apply logistic regression models in Python as well as how to interpret logistic regression results.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores statistical and machine learning algorithms, which are standard in industry
Led by Sebastian Thrun and Josh Bernhard, who are recognized for their work in machine learning
Builds a strong foundation for beginners in statistical and machine learning algorithms
May require learners to take introductory math and probability courses first
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Activities
Coming soon
We're preparing activities for
Algorithms.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Algorithms will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models to solve complex problems. Take this course to help build a foundation in the fundamentals of machine learning algorithms, particularly focusing on regression techniques, that can be used to create accurate and efficient models.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to help businesses and organizations make informed decisions. Take this course to help build a foundation in the fundamentals of statistical and machine learning algorithms that can be used to analyze data and make informed decisions.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to data in the field of biology. Take this course to help build a foundation in the methods of using statistical and machine learning algorithms to analyze biological data and make informed decisions about medical treatments and outcomes.
Quantitative Analyst
Quantitative Analyst
Quantitative Analyst help organizations make optimal decisions about everything from how much of any particular item they should buy to how much of a certain good they should produce. Take this course to help build a foundation in the methods of analyzing quantitative data and identifying trends to make more accurate predictions about future outcomes.
Data Engineer
Data Engineer
Data Engineers design, develop, and implement data pipelines to ensure the availability and quality of data for analysis. Take this course to help build a foundation in the methods of using statistical and machine learning algorithms to improve the efficiency of data pipelines.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and patterns of health and disease in populations. Take this course to help build a foundation in the methods of using statistical and machine learning algorithms to analyze data and identify trends and patterns in health and disease.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use analytical techniques to help businesses and organizations make better decisions about how to allocate resources. Take this course to help build a foundation in the methods of using statistical and machine learning algorithms to solve complex optimization problems.
Data Scientist
Data Scientist
Data Scientists observe relationships between data points and create solutions from their findings. Take this course to help build a foundation in the methods of gathering, cleaning, and analyzing structured data to ultimately analyze its significance.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and mitigate risks to help businesses and organizations make informed decisions. Take this course to help build a foundation in the methods of using statistical and machine learning algorithms to analyze data and identify potential risks.
Actuary
Actuary
Actuaries analyze the probability of future events to determine insurance rates and investment risks. Take this course to help build a foundation in the fundamentals of using and interpreting data to make sound decisions about insurance rates and investment risks.
Business Analyst
Business Analyst
Business Analysts analyze business requirements and develop solutions to improve efficiency. Take this course to help build a foundation in the methods of using statistical and machine learning algorithms to make data-driven decisions that improve business outcomes.
Data Analyst
Data Analyst
Data Analysts help refine existing models to increase their efficiency by analyzing large data sets and creating solutions to improve processes. Take this course to help build a foundation in the methods of using and interpreting data to improve the efficiency of various processes within an organization.
Financial Analyst
Financial Analyst
Financial Analysts help businesses and individuals plan for the future by analyzing data and making financial recommendations. Take this course to help build a foundation in the fundamentals of using and interpreting data to make sound financial decisions.
Market Researcher
Market Researcher
Market Researchers study the demand, public perception, and behavior to provide businesses with insights that will give them an advantage in the market. Take this course to help build a foundation in the fundamentals of statistical and machine learning models that are used to analyze data and make informed marketing decisions.
Software Engineer
Software Engineer
Software Engineers design, develop, and implement software systems. Take this course to help build a foundation in the methods of applying statistical and machine learning algorithms to find efficient solutions to complex problems.
For more career information including salaries, visit:
OpenCourser.com/course/8mzl86/algorithm
Reading list
We've selected 11 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
Algorithms.
Provides a practical guide to regression analysis, including linear regression, multiple linear regression, and logistic regression.
Provides a comprehensive overview of statistical learning methods, including linear regression, multiple linear regression, and logistic regression.
Provides a comprehensive overview of regression analysis, including linear regression, multiple linear regression, and logistic regression.
Classic text on statistical learning, providing a more in-depth treatment of the topics covered in the course.
Provides a comprehensive overview of regression modeling with actuarial and financial applications, including linear regression, multiple linear regression, and logistic regression.
Provides a comprehensive overview of generalized linear models, including linear regression, multiple linear regression, and logistic regression.
Provides a practical guide to implementing machine learning algorithms in Python, including linear regression, multiple linear regression, and logistic regression.
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Provides a comprehensive overview of deep learning, including a discussion of linear regression, multiple linear regression, and logistic regression.
Provides a comprehensive overview of reinforcement learning, including a discussion of linear regression, multiple linear regression, and logistic regression.
Provides a comprehensive overview of Bayesian reasoning and machine learning, including a discussion of linear regression, multiple linear regression, and logistic regression.
Save
Provides a comprehensive overview of econometrics, including a discussion of linear regression, multiple linear regression, and logistic regression.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8mzl86/algorithm
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Time
900 hours
Level
Introductory
Via
Udacity
Instructors
Sebastian Thrun
Josh Bernhard
Language
English
Good to know
Explores statistical and machine learning algorithms, which are standard in industry
Led by Sebastian Thrun and Josh Bernhard, who are recognized for their work in machine learning
Builds a strong foundation for beginners in statistical and machine learning algorithms
May require learners to take introductory math and probability courses first
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