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Better Software Through Measurement
Brendan Younger
Brendan Younger
This course will show you how to generate recommendations for your users, filter messages based on users' preferences, decide which web page performs best, keep track of timings in your application, and discover groups among items.
Read more
This course will show you how to generate recommendations for your users, filter messages based on users' preferences, decide which web page performs best, keep track of timings in your application, and discover groups among items.
Read more
This course will show you how to generate recommendations for your users, filter messages based on users' preferences, decide which web page performs best, keep track of timings in your application, and discover groups among items.
This course will show you how to generate recommendations for your users, filter messages based on users' preferences, decide which web page performs best, keep track of timings in your application, and discover groups among items. These techniques are at the heart of many of the largest search engines and online retailers, but can be used to good effect for smaller companies. Throughout the course, the emphasis will be on examining and extending working sample code. The algorithms will be presented intuitively and you do not need any advanced math background.
Register for this course and see more details by visiting:
OpenCourser.com/course/g5od8w/better
What's inside
Syllabus
Instrumentation: Streaming Metrics
Optimizing Conversion: A/B Testing
Recommendations: Item-based Recommendations
Personalized Recommendations: Naive Bayesian Classifier
Read more
Syllabus
Instrumentation: Streaming Metrics
Optimizing Conversion: A/B Testing
Recommendations: Item-based Recommendations
Personalized Recommendations: Naive Bayesian Classifier
Read more
Finding Groups: k-means Clustering
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides the tools to explore a variety of use cases for machine learning
Teaches foundational skills for data scientists or anybody curious about data, exploring use cases that translate well to business analytics
Offers hands-on labs and interactive materials for reinforcement
Recommended as a prerequisite before taking course
Some of the provided use cases might quickly become obsolete
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Activities
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Better Software Through Measurement.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Better Software Through Measurement will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. This course provides a foundation in data analysis and machine learning techniques that can help Data Scientists make better use of data. For example, the course covers how to use clustering algorithms to identify groups of similar users, which can help Data Scientists develop targeted marketing campaigns.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make better decisions. This course provides a foundation in data analysis and visualization techniques that can help Business Analysts communicate insights to stakeholders. For example, the course covers how to use data visualization tools to create charts and graphs that can help Business Analysts communicate complex data in a clear and concise way.
Product Manager
Product Manager
Product Managers are responsible for planning, developing, and launching new products. This course provides a foundation in user experience research and data analysis techniques that can help Product Managers make better decisions about product design and development. For example, the course covers how to use A/B testing to compare different versions of a product, which can help Product Managers identify the version that is most likely to be successful.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. This course provides a foundation in software measurement techniques that can help Software Engineers improve the quality and performance of their software. For example, the course covers how to measure and optimize application performance, which can help Software Engineers ensure that their applications are running efficiently and meeting user needs.
User Experience Researcher
User Experience Researcher
User Experience Researchers study how users interact with products and services. This course provides a foundation in user research and data analysis techniques that can help User Experience Researchers make better decisions about product design. For example, the course covers how to use usability testing to identify problems with product design, which can help User Experience Researchers improve the user experience.
Statistician
Statistician
Statisticians use data to draw conclusions about the world. This course provides a foundation in statistical analysis techniques that can help Statisticians make better use of data. For example, the course covers how to use regression analysis to identify relationships between variables, which can help Statisticians make predictions about future events.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. This course provides a foundation in data analysis and visualization techniques that can help Marketing Analysts make better decisions about marketing strategy. For example, the course covers how to use segmentation analysis to identify different groups of customers, which can help Marketing Analysts develop targeted marketing campaigns.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines. This course provides a foundation in data engineering techniques that can help Data Engineers build and maintain more efficient and reliable data pipelines. For example, the course covers how to use data streaming technologies to process data in real time, which can help Data Engineers build data pipelines that can handle large volumes of data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. This course provides a foundation in machine learning algorithms and techniques that can help Machine Learning Engineers build and maintain more accurate and efficient machine learning models. For example, the course covers how to use neural networks to build machine learning models that can recognize objects in images, which can help Machine Learning Engineers build self-driving cars and other autonomous systems.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use data to make investment decisions. This course provides a foundation in data analysis and modeling techniques that can help Quantitative Analysts make better investment decisions. For example, the course covers how to use machine learning algorithms to predict stock prices, which can help Quantitative Analysts identify undervalued stocks.
Systems Analyst
Systems Analyst
Systems Analysts design and implement computer systems. This course provides a foundation in systems analysis and design techniques that can help Systems Analysts build and maintain more efficient and effective computer systems. For example, the course covers how to use object-oriented design techniques to build computer systems that are more flexible and maintainable, which can help Systems Analysts build computer systems that can meet the changing needs of businesses.
Information Architect
Information Architect
Information Architects design and organize websites and other information systems. This course provides a foundation in data analysis and visualization techniques that can help Information Architects make better decisions about information architecture. For example, the course covers how to use card sorting to understand how users organize information, which can help Information Architects create more user-friendly websites and information systems.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical models to solve business problems. This course provides a foundation in operations research techniques that can help Operations Research Analysts build and maintain more efficient and effective business processes. For example, the course covers how to use linear programming to optimize resource allocation, which can help Operations Research Analysts improve the efficiency of supply chains and other business processes.
For more career information including salaries, visit:
OpenCourser.com/course/g5od8w/better
Reading list
We've selected nine 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
Better Software Through Measurement.
Save
A comprehensive textbook that covers the theory and practice of data mining, including data preprocessing, data mining algorithms, and data visualization. It's a valuable reference for learners who want to gain a deeper understanding of data mining techniques.
A comprehensive textbook that covers the theory and practice of statistical learning, including supervised learning, unsupervised learning, and statistical modeling. It's a valuable reference for learners who want to gain a deeper understanding of statistical learning techniques.
Provides practical guidance on implementing machine learning algorithms using popular Python libraries. It's a valuable resource for learners who want to apply machine learning techniques to real-world problems.
Provides practical guidance on implementing machine learning algorithms using the Python programming language. It's a great resource for learners who want to apply machine learning techniques to real-world problems using Python.
Provides practical guidance on implementing machine learning algorithms using the R programming language. It's a great resource for learners who want to apply machine learning techniques to real-world problems using R.
Provides practical guidance on natural language processing using the Python programming language. It's a great resource for learners who want to apply natural language processing techniques to real-world problems using Python.
Provides practical guidance on data analysis using the Pandas library in Python. It's a great resource for learners who want to gain proficiency in data manipulation and analysis using Python.
Save
Provides practical guidance on data science using AWS. It's a great resource for learners who want to apply data science techniques to real-world problems using AWS.
Covers the fundamentals of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It's a great resource for learners who want to understand the theory and applications of deep learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/g5od8w/better
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Time
97 hours
Level
Intermediate
Via
Pluralsight
Instructor
Brendan Younger
Language
English
Good to know
Provides the tools to explore a variety of use cases for machine learning
Teaches foundational skills for data scientists or anybody curious about data, exploring use cases that translate well to business analytics
Offers hands-on labs and interactive materials for reinforcement
Recommended as a prerequisite before taking course
Some of the provided use cases might quickly become obsolete
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