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Anton Savostianov
Hi! Our online course aims to provide necessary background in Calculus sufficient for up-following Data Science courses. Course starts with a basic introduction to concepts concerning functional mappings. Later students are assumed to study limits (in case...
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Hi! Our online course aims to provide necessary background in Calculus sufficient for up-following Data Science courses. Course starts with a basic introduction to concepts concerning functional mappings. Later students are assumed to study limits (in case of sequences, single- and multivariate functions), differentiability (once again starting from single variable up to multiple cases), integration, thus sequentially building up a base for the basic optimisation. To provide an understanding of the practical skills set being taught, the course introduces the final programming project considering the usage of optimisation routine in machine learning. Additional materials provided during the course include interactive plots in GeoGebra environment used during lectures, bonus reading materials with more general methods and more complicated basis for discussed themes. This Course is part of HSE University Master of Data Science degree program. Learn more about the admission into the program and how your Coursera work can be leveraged if accepted into the program here https://inlnk.ru/rj64e.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a strong foundation for beginners in Calculus, making it suitable for those new to the subject
Develops essential calculus skills for data science, which is highly relevant to the industry
Taught by an experienced instructor, Anton Savostianov, who is recognized for his expertise in Calculus
Requires learners to have basic mathematics knowledge, which may not be suitable for complete beginners
Provides hands-on experience through a programming project, which is beneficial for practical application
Offers interactive plots in GeoGebra environment, which enhances the learning experience

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Reviews summary

Theoretical math prerequisites for data science

The "Calculus and Optimization for Machine Learning" course is generally well received by students. Many reviews mention that the course provides a solid foundation in calculus for those pursuing data science. The course covers topics such as limits, derivatives, integrals, and optimization. Students appreciate the clear explanations and interactive plots in the GeoGebra environment. However, some students have difficulty understanding the instructor's accent and find the workload to be heavy. Overall, this course is recommended for students with a background in calculus who are looking to reinforce their understanding or refresh their skills.
GeoGebra plots provide useful visuals.
""interactive plots in GeoGebra environment used during lectures""
Explanations and lectures are clear.
""lectures were little off but concept wise it was good though it could be better""
""Topics are well explained in the lectures and with help from the discussions I succeeded""
Instructor's accent is difficult to understand.
""The professor mumbles and his english is lackluster""
""Sometimes it's hard to understand lecturer due to poor English""
Coursework can be demanding.
""I found the course quite difficult""
""This course has a lot of overhead""

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 Calculus and Optimization for Machine Learning with these activities:
Organize your Calculus notes and materials
Staying organized will help you find the information you need quickly and easily.
Browse courses on Calculus
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  • Create a system for organizing your notes and materials
  • File your notes and materials in a logical way
  • Keep your notes and materials up to date
Review your notes on functions
Reviewing your notes will help strengthen your understanding of the concepts of functions and their graphs.
Browse courses on Functions
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  • Gather your notes on functions.
  • Review the definitions of different types of functions, such as linear, quadratic, and polynomial functions.
  • Go over the graphs of different types of functions.
  • Practice identifying the key features of functions, such as intercepts, slopes, and turning points.
Brush up on the basics of Calculus
Reviewing the fundamentals of Calculus will provide a solid foundation for the more advanced topics covered in this course.
Show steps
  • Go over your notes from previous Calculus courses
  • Take practice problems on differentiation and integration
  • Review online resources or textbooks on Calculus
12 other activities
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Read and review 'Calculus: Early Transcendentals' by James Stewart
This textbook provides a comprehensive and well-written introduction to Calculus.
Show steps
  • Read each chapter carefully and take notes
  • Solve the practice problems at the end of each chapter
  • Review the key concepts and formulas regularly
Watch video tutorials on limits
Watching video tutorials will provide you with a clear and concise explanation of the concept of limits.
Browse courses on Limits
Show steps
  • Search for video tutorials on limits on YouTube or other online platforms.
  • Watch the tutorials and take notes on the key concepts.
  • Pause the videos and rewind as needed to fully understand the explanations.
Follow video tutorials on Calculus concepts
Watching video tutorials can help you visualize and understand complex Calculus concepts more easily.
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  • Search for video tutorials on specific Calculus topics you're struggling with
  • Take notes or summarize the main points of the tutorials
  • Try to apply the concepts you've learned to practice problems
Join a study group or find a Calculus tutor
Collaborating with peers or receiving guidance from a tutor can enhance your understanding and problem-solving skills.
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  • Find a study group or tutor who aligns with your learning style
  • Attend study sessions or tutoring regularly
  • Actively participate in discussions and ask questions
Discuss optimization techniques with classmates
Discussing optimization techniques with classmates will help you gain different perspectives and insights on the subject.
Browse courses on Optimization
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  • Find a study group or form a group with classmates.
  • Choose a specific optimization technique to discuss.
  • Prepare for the discussion by reading relevant materials and coming up with questions.
  • Meet with your group and discuss the topic, sharing your ideas and insights.
Solve practice problems on derivatives
Solving practice problems will help you develop your skills in finding derivatives of functions.
Browse courses on Derivatives
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  • Find practice problems on derivatives from textbooks, online resources, or your instructor.
  • Attempt to solve the problems on your own.
  • Check your answers against the provided solutions.
  • Review your mistakes and go over the concepts again if needed.
Solve Calculus practice problems
Regular practice is essential for mastering Calculus. Aim to solve a variety of problems to enhance your understanding.
Browse courses on Calculus
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  • Find practice problems in your textbook or online
  • Start with easier problems and gradually move on to more challenging ones
  • Check your answers and identify areas where you need more practice
Create a study guide or summary of key Calculus concepts
Creating a study guide or summary will help you organize and retain the key concepts covered in the course.
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  • Identify the most important concepts from each lesson
  • Summarize the concepts in your own words
  • Organize the concepts into a logical structure
  • Review your study guide regularly
Write a summary of the main concepts in integration
Writing a summary will help you consolidate your understanding of the main concepts in integration.
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  • Review your notes and textbooks on integration.
  • Identify the key concepts and main ideas in integration.
  • Write a clear and concise summary of these concepts.
  • Proofread your summary for any errors.
Mentor a Calculus student or tutor a younger student
Teaching others can reinforce your understanding of Calculus and develop your communication and problem-solving skills.
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  • Find a student who needs help with Calculus
  • Determine the student's strengths and weaknesses
  • Develop a plan to help the student improve their Calculus skills
  • Meet with the student regularly to provide guidance and support
Contribute to an open-source Calculus project
Working on an open-source project will provide you with hands-on experience and contribute to the Calculus community.
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  • Find an open-source Calculus project that interests you
  • Review the project's documentation and codebase
  • Identify an area where you can contribute
  • Submit your contributions to the project
Contribute to an open-source project related to data science
Contributing to an open-source project will give you hands-on experience in applying data science techniques.
Browse courses on Data Science
Show steps
  • Find an open-source project related to data science.
  • Identify an area where you can contribute.
  • Follow the project's contribution guidelines.
  • Submit your contribution for review.

Career center

Learners who complete Calculus and Optimization for Machine Learning will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Machine Learning Engineers. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Machine Learning Engineer.
Data Scientist
Data Scientists use scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Data Scientists. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Data Scientist.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make investment decisions. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Quantitative Analysts. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Quantitative Analyst.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex problems in various industries. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Operations Research Analysts. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of an Operations Research Analyst.
Financial Analyst
Financial Analysts use financial data and models to make investment recommendations and decisions. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Financial Analysts. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Financial Analyst.
Statistician
Statisticians collect, analyze, and interpret data to make informed decisions. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Statisticians. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Statistician.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Data Analysts. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Data Analyst.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty in various fields, including insurance, finance, and healthcare. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Actuaries. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of an Actuary.
Business Analyst
Business Analysts use data and analytical techniques to solve business problems. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Business Analysts. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Business Analyst.
Risk Analyst
Risk Analysts use mathematical and statistical techniques to assess and manage risk in various industries. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Risk Analysts. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Risk Analyst.
Economist
Economists study the production, distribution, and consumption of goods and services. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Economists. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of an Economist.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Software Engineers. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Software Engineer.
Teacher
Teachers educate students in various subjects. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Teachers. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Teacher.
Product Manager
Product Managers manage the development and launch of new products. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Product Managers. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Product Manager.
Consultant
Consultants provide expert advice to businesses and organizations. This course can help build a foundation in Calculus and Optimization, which are essential mathematical concepts for Consultants. It covers topics such as limits, differentiability, integration, and optimization, which are all relevant to the work of a Consultant.

Reading list

We've selected 12 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 Calculus and Optimization for Machine Learning.
Rigorous introduction to calculus, covering topics such as limits, derivatives, integrals, and differential equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to convex optimization, covering topics such as linear programming, nonlinear programming, and semidefinite programming. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to calculus, covering topics such as limits, derivatives, integrals, and differential equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to single-variable calculus, covering topics such as limits, derivatives, integrals, and differential equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to multivariable calculus, covering topics such as partial derivatives, multiple integrals, and vector calculus. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to calculus, covering topics such as limits, derivatives, integrals, and differential equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to calculus, covering topics such as limits, derivatives, integrals, and differential equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to pattern recognition and machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to linear algebra, covering topics such as vectors, matrices, and linear transformations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to differential equations, covering topics such as first-order equations, second-order equations, and systems of equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.
Comprehensive introduction to mathematical methods used in physics and engineering, covering topics such as calculus, linear algebra, and differential equations. It is written in a clear and concise style, and includes numerous examples and exercises to help students understand the material.

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