
The University of Sydney
Skills you'll gain: Advanced Mathematics, Integral Calculus, Calculus, Mathematical Theory & Analysis, Differential Equations, Applied Mathematics, Engineering Calculations, Mathematical Modeling, Linear Algebra, Physics, Derivatives
Intermediate · Course · 1 - 4 Weeks

The Hong Kong University of Science and Technology
Skills you'll gain: Differential Equations, Linear Algebra, Matlab, Engineering Calculations, Engineering Analysis, Numerical Analysis, Finite Element Methods, Integral Calculus, Mathematical Software, Mechanical Engineering, Calculus, electromagnetics, Algebra, Applied Mathematics, Mathematical Modeling, Engineering, Simulation and Simulation Software, Advanced Mathematics, Geometry, Computational Thinking
Beginner · Specialization · 3 - 6 Months

Imperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives
Beginner · Specialization · 3 - 6 Months

Johns Hopkins University
Skills you'll gain: Linear Algebra, Algebra, Applied Mathematics, Advanced Mathematics, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Engineering Analysis, Mathematical Theory & Analysis, Numerical Analysis, Geometry, Data Transformation, Applied Machine Learning, Dimensionality Reduction, Markov Model, Probability
Beginner · Specialization · 3 - 6 Months

Johns Hopkins University
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Science, Statistics, Mathematical Modeling, Data Analysis, Data Modeling, Applied Mathematics
Advanced · Specialization · 3 - 6 Months

Skills you'll gain: International Financial Reporting Standards, Business Valuation, Consolidation, Technical Accounting, Financial Reporting, Financial Analysis, Financial Accounting, Mergers & Acquisitions, Financial Statement Analysis, Income Statement, Accounting, Balance Sheet
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Excel Macros, Data Validation, Scatter Plots, Pivot Tables And Charts, Microsoft Excel, Data Visualization, Regression Analysis, Excel Formulas, Histogram, Data Analysis, Data Integrity, Descriptive Statistics, Data Visualization Software, Spreadsheet Software, Analytics, Statistical Analysis, Data Analysis Expressions (DAX), Statistical Methods, Descriptive Analytics, Automation
Beginner · Specialization · 1 - 3 Months

Johns Hopkins University
Skills you'll gain: Calculus, Integral Calculus, Advanced Mathematics, Mathematical Theory & Analysis, Applied Mathematics, Numerical Analysis, Mathematical Modeling, Derivatives
Intermediate · Course · 1 - 3 Months

Johns Hopkins University
Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Artificial Intelligence, Probability, Regression Analysis, Calculus, Statistical Analysis, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Statistical Modeling, Machine Learning Algorithms, Dimensionality Reduction
Beginner · Course · 1 - 3 Months

Universitat Politècnica de València
Skills you'll gain: Integral Calculus, Calculus, General Mathematics, Engineering Calculations, Trigonometry
Beginner · Course · 1 - 3 Months

Johns Hopkins University
Skills you'll gain: Algebra, Mathematical Modeling, Graphing, Arithmetic, Advanced Mathematics, Applied Mathematics, General Mathematics, Analytical Skills, Probability & Statistics, Geometry
Beginner · Specialization · 3 - 6 Months

University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning
Build toward a degree
Beginner · Specialization · 1 - 3 Months
Advanced mathematics refers to higher-level mathematical concepts that go beyond basic arithmetic and algebra. It includes subjects such as calculus, linear algebra, differential equations, and abstract algebra. These areas provide the theoretical foundation for many disciplines, including engineering, physics, computer science, and economics.
Understanding advanced mathematics is important because it enables complex problem-solving, logical reasoning, and data analysis. These skills are essential for developing algorithms, modeling real-world systems, and making informed decisions in today’s increasingly data-driven and technology-focused world.‎
A background in advanced mathematics opens doors to numerous career opportunities. Professionals with expertise in this area can pursue roles such as data analyst, quantitative researcher, financial analyst, operations researcher, and software engineer. These positions often require strong analytical skills and the ability to apply mathematical principles to real-world problems. Additionally, advanced mathematics is highly valued in academia, where individuals can engage in research or teaching roles, contributing to the development of future mathematicians and scientists.‎
Success in advanced mathematics requires a solid foundation in core concepts such as algebra, geometry, and calculus. Key skills include problem-solving, critical thinking, and the ability to work with abstract concepts. Familiarity with mathematical software and programming languages, such as Python or R, can also be beneficial, especially in fields like data science and engineering. Engaging in practice problems and collaborating with peers can further enhance your learning experience and confidence in applying advanced mathematical techniques.‎
There are several excellent online courses available for those interested in advanced mathematics. For instance, the Mathematics for Engineering Specialization provides a comprehensive overview of mathematical principles applied in engineering contexts. Another option is the Mathematics for Machine Learning and Data Science Specialization, which focuses on the mathematical foundations necessary for machine learning applications. These courses are designed to cater to various learning styles and schedules, making them accessible to a global audience.‎
Yes. You can start learning advanced mathematics on Coursera for free in two ways:
If you want to keep learning, earn a certificate in advanced mathematics topics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
Learning advanced mathematics requires a structured approach. Start by reviewing foundational concepts and gradually progress to more complex topics. Utilize online resources, textbooks, and practice problems to reinforce your understanding. Joining study groups or online forums can provide additional support and motivation. Setting specific goals and tracking your progress can help maintain focus and encourage self-empowerment throughout your learning journey.‎
Advanced mathematics courses typically cover a variety of topics, including calculus, linear algebra, differential equations, probability theory, and statistics. Some courses may also explore specialized areas such as numerical analysis, optimization, and mathematical modeling. These topics are essential for understanding complex systems and solving real-world problems, making them integral to various academic and professional fields.‎
For training and upskilling employees, courses like the Mathematics for Engineers Specialization can be particularly beneficial. This specialization focuses on mathematical techniques applicable in engineering contexts, enhancing problem-solving skills and analytical thinking. Additionally, the Probabilistic Graphical Models Specialization equips learners with the mathematical and statistical skills necessary, making it a valuable resource for workforce development.‎