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Math For Programmers
Simon Robinson
Simon Robinson
This course covers the maths behind how your computer stores and manipulates data. You'll learn how to read binary and hexadecimal, how both integers and floating point numbers are stored and the limitations of using them. Advice on best practices and how to work effectively with boolean values and bitwise operators.
Read more
This course covers the maths behind how your computer stores and manipulates data. You'll learn how to read binary and hexadecimal, how both integers and floating point numbers are stored and the limitations of using them. Advice on best practices and how to work effectively with boolean values and bitwise operators.
Read more
This course covers the maths behind how your computer stores and manipulates data. You'll learn how to read binary and hexadecimal, how both integers and floating point numbers are stored and the limitations of using them. Advice on best practices and how to work effectively with boolean values and bitwise operators.
Have you ever wondered exactly why displaying the contents of memory often gives strange-looking numbers like 0x38FF that contain letters? Or puzzled over a time when your code added two floating point numbers but the result wasn't quite correct? If so, then this is the course for you.
This course aims to teach you the mathematics behind how computers store and manipulate numbers and booleans. You'll learn, amongst other things:
In this course you will learn about:
Binary is a number system made up of only 0s and 1s, which represent "off" or "on" respectively. This allows numbers to be represented physically inside the computer, which makes it possible for the device to perform calculation. Binary is used to write data, like instructions for the computer processor.
Hexadecimal, or hex, is a number system that uses 16 as its base, rather than 10. Rather than just using the digits 0-9, it also uses letters A-F to represent values of ten to fifteen. Hexadecimal simplifies how binary is represented, so an 8-bit binary number becomes a 2-digit hex number.
This course is for anyone who wants to learn the mathematics behind how computers store and manipulate numbers and booleans! It is also great if you are trying to learn how to read binary and hexadecimal numbers.
There are no strict prerequisites to this course, but it is intermediate level material, so come prepared to exercise those mental muscles!
Register for this course and see more details by visiting:
OpenCourser.com/course/kyj92f/math
What's inside
Syllabus
Math for Programmers
Types of Data
Working in Binary
Integers
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Syllabus
Math for Programmers
Types of Data
Working in Binary
Integers
Read more
Floating Point Numbers
Logic, Booleans and Bitwise Operations
Errors and Accuracy
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on mathematical principles, which are universal to computer science and engineering
Provides practical advice and guidance on handling data types in programming
Tends to an audience with a background in mathematics or coding
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Math For Programmers.
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Career center
Learners who complete Math For Programmers will develop knowledge and skills
that may be useful to these careers:
Computer Scientist
Computer Scientist
Computer Scientists design, develop, and analyze computer systems. They typically have a strong background in mathematics, computer science, and engineering. This course provides a solid foundation in the mathematical concepts used in computer science, and may be useful for Computer Scientists who wish to gain a deeper understanding of these concepts.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They typically have a strong foundation in computer science and mathematics, and may specialize in areas such as artificial intelligence, data science, and web development. This course provides an understanding of the mathematical concepts used in software development, which can help Software Engineers write more efficient and reliable code.
Quant Analyst
Quant Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. They typically have a strong background in mathematics, statistics, and computer science. This course provides a solid foundation in the mathematical concepts used in quantitative finance, and may be useful for Quant Analysts who wish to gain a deeper understanding of these concepts.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They typically have a strong background in mathematics, statistics, and computer science. This course provides a solid foundation in the mathematical concepts used in machine learning, and may be useful for Machine Learning Engineers who wish to gain a deeper understanding of these concepts.
Data Scientist
Data Scientist
Data Scientists combine statistics, domain expertise, and advanced computing techniques to extract insights from datasets and build machine learning models. For this role in particular, proficiency with advanced mathematics, integers, floating point numbers, logic, and bitwise operations is required. This course helps build a foundation in these areas and may be useful for Data Scientists.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They typically have a strong background in mathematics, statistics, and computer science. This course provides a foundation in the mathematical concepts used in statistics, and may be useful for Statisticians who wish to gain a deeper understanding of these concepts.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They typically have a strong background in mathematics, statistics, and computer science. This course provides a foundation in the mathematical concepts used in data analysis, and may be useful for Data Analysts who wish to gain a deeper understanding of these concepts.
Cryptographer
Cryptographer
Cryptographers develop and analyze algorithms for secure communication. They typically have a strong background in mathematics, computer science, and statistics. This course provides a solid foundation in the mathematical concepts used in cryptography, and may be useful for Cryptographers who wish to gain a deeper understanding of these concepts.
Artificial Intelligence Researcher
Artificial Intelligence Researcher
Artificial Intelligence Researchers develop new theories and algorithms for artificial intelligence. They typically have a strong background in mathematics, computer science, and statistics. This course provides a solid foundation in the mathematical concepts used in artificial intelligence, and may be useful for Artificial Intelligence Researchers who wish to gain a deeper understanding of these concepts.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve complex problems in business and industry. They typically have a strong background in mathematics, statistics, and computer science. This course provides a foundation in the mathematical concepts used in operations research, and may be useful for Operations Research Analysts who wish to gain a deeper understanding of these concepts.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to solve problems in biology and medicine. They typically have a strong background in mathematics, statistics, and biology. This course provides a foundation in the mathematical concepts used in biostatistics, and may be useful for Biostatisticians who wish to gain a deeper understanding of these concepts.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They typically have a strong background in mathematics, statistics, and finance. This course provides a foundation in the mathematical concepts used in actuarial science, and may be useful for Actuaries who wish to gain a deeper understanding of these concepts.
Market Researcher
Market Researcher
Market Researchers conduct research to understand consumer behavior and preferences. They typically have a strong background in mathematics, statistics, and marketing. This course provides a foundation in the mathematical concepts used in market research, and may be useful for Market Researchers who wish to gain a deeper understanding of these concepts.
Economist
Economist
Economists study the production, distribution, and consumption of goods and services. They typically have a strong background in mathematics, statistics, and economics. This course provides a foundation in the mathematical concepts used in economics, and may be useful for Economists who wish to gain a deeper understanding of these concepts.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data and make investment recommendations. They typically have a strong background in mathematics, statistics, and economics. This course provides a foundation in the mathematical concepts used in financial analysis, and may be useful for Financial Analysts who wish to gain a deeper understanding of these concepts.
For more career information including salaries, visit:
OpenCourser.com/course/kyj92f/math
Reading list
We've selected 23 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
Math For Programmers.
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This classic textbook provides a comprehensive guide to discrete mathematics, including coverage of number theory and algebra. It good resource for anyone who wants to learn more about the mathematical foundations of computer science.
Is helpful for background knowledge on computer architecture, which underpins how data is stored and manipulated by computers. It can serve as a reference for understanding the hardware side of data representation.
This textbook provides a comprehensive guide to discrete mathematics, including coverage of number theory and algebra. It good resource for anyone who wants to learn more about the mathematical foundations of computer science.
Covers the fundamental concepts of operating systems, including memory management, process scheduling, and file systems, which are important for understanding how data is managed and manipulated by the computer.
This textbook provides a comprehensive guide to discrete mathematics, including coverage of number theory and algebra. It good resource for anyone who wants to learn more about the mathematical foundations of computer science.
This textbook provides a comprehensive guide to discrete mathematics, including coverage of number theory and algebra. It good resource for anyone who wants to learn more about the mathematical foundations of computer science.
This textbook provides a comprehensive guide to algebra, with a focus on applications in computer science. It good resource for anyone who wants to learn more about the mathematical foundations of computer science.
This textbook provides a comprehensive overview of digital design and computer architecture, including coverage of number representation and arithmetic. It good resource for anyone who wants to learn more about the hardware and software that make up a computer.
This popular textbook provides a comprehensive overview of computer architecture, including coverage of number representation and arithmetic. It good resource for anyone who wants to learn more about the hardware and software that make up a computer.
Provides a comprehensive coverage of data structures and algorithms, which are essential for understanding how data is organized and processed in computers. It would prove useful as a reference for various data structures and algorithms.
Provides a comprehensive guide to algorithm design, including coverage of number representation and arithmetic. It good resource for anyone who wants to learn more about the algorithms that are used in computer science.
Provides deep technical detail on the implementation of computer arithmetic algorithms in hardware. This text classic and advanced treatment of the subject and is best used as a secondary reference.
This textbook introduces the fundamental concepts of computer science, including number representation and arithmetic. It good resource for anyone who wants to learn more about the basics of computer science.
Provides a collection of programming interview questions and solutions, including questions on number representation and arithmetic. It good resource for anyone who is preparing for a job interview in the tech industry.
Is considered a classic in the field of algorithms and provides a comprehensive coverage of various algorithm design techniques. It can serve as a reference for understanding the algorithms behind data processing.
Focuses on the programmer's perspective of computer systems and provides a detailed overview of the hardware and software components of a computer. It can provide additional insights into how data is stored and manipulated at the system level.
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Provides a comprehensive coverage of digital design principles and practices, which are essential for understanding the hardware implementation of data storage and manipulation. It can serve as a reference for low-level details of data representation.
Introduces numerical methods, which are essential for solving mathematical problems on computers. It covers topics such as interpolation, integration, and differential equations, which can be useful for understanding how data is processed and analyzed.
Provides a comprehensive coverage of probability and statistics from a computer science perspective. It covers topics such as probability distributions, random variables, and statistical inference, which can be useful for understanding how data is analyzed and interpreted.
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Introduces data mining concepts and techniques, which are essential for understanding how data is processed and analyzed to extract meaningful insights. It can be useful for exploring advanced topics in data manipulation and analysis.
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Provides a comprehensive coverage of deep learning concepts and techniques. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks, which can be useful for understanding how data is analyzed and processed in the context of deep learning.
Provides a comprehensive coverage of reinforcement learning concepts and techniques. It covers topics such as Markov decision processes, value functions, and policy optimization, which can be useful for understanding how data is used to train reinforcement learning models.
Introduces natural language processing concepts and techniques using Python. It covers topics such as text preprocessing, natural language understanding, and natural language generation, which can be useful for understanding how data is processed and analyzed in the context of natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/kyj92f/math
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Mathematics for Computer Science
Time
316 hours
Level
Intermediate
Via
Pluralsight
Instructor
Simon Robinson
Language
English
Good to know
Focuses on mathematical principles, which are universal to computer science and engineering
Provides practical advice and guidance on handling data types in programming
Tends to an audience with a background in mathematics or coding
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