Master the essential mathematical foundations essential for careers in engineering, data science and artificial intelligence. The Mathematics for Engineering specialisation builds systematic competencies in calculus, probability, linear algebra, discrete mathematics, and formal logic, preparing you to solve complex technical problems and develop cutting-edge algorithms. Whether you're beginning your quantitative journey or strengthening existing skills, this specialisation provides the essential mathematical literacy required for advanced applications in engineering, data science, algorithm design, and artificial intelligence across various technical domains.

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Spécialisation Mathematics for Engineering
Mathematical Foundations for an Engineering Career. Master core mathematical skills essential for advanced careers in technical domains.

Instructeur : BITS Pilani Instructors Group
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Ce que vous apprendrez
Master calculus, trigonometry, matrices, differential equations, and algebraic techniques essential for engineering and data science.
Apply probability theory, statistical distributions, hypothesis testing, and confidence intervals to analyze data and validate findings.
Develop logical thinking through mathematical proofs, discrete structures, graph theory, and formal verification techniques.
Solve optimization problems using linear algebra, eigenvalue analysis, and mathematical modeling for machine learning applications.
Vue d'ensemble
Compétences que vous acquerrez
- Engineering Calculations
- Artificial Intelligence and Machine Learning (AI/ML)
- Deductive Reasoning
- Descriptive Analytics
- Programming Principles
- Analytics
- Engineering Analysis
- Statistical Inference
- Bayesian Statistics
- Theoretical Computer Science
- Data Analysis
- Calculus
- Logical Reasoning
- Differential Equations
- Trigonometry
- Statistical Analysis
- Computational Logic
- Statistical Modeling
- Probability & Statistics
- Linear Algebra
Ce qui est inclus

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août 2025
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Spécialisation - série de 5 cours
Ce que vous apprendrez
Integrate trigonometric concepts to analyse and solve complex real-world engineering problems.
Critically evaluate and solve intricate systems of linear equations using matrix operations.
Synthesise the principles of differentiation and integration to develop and optimise engineering models.
Formulate and solve first-order and first-degree differential equations to effectively model a variety of engineering processes.
Compétences que vous acquerrez
Ce que vous apprendrez
Evaluate and interpret complex data sets with probabilistic models, applying Bayes’ theorem and Chebyshev’s inequality to solve real-world problems.
Design hypothesis tests, including t-tests, z-tests, and chi-square tests, to validate data-driven hypotheses in various professional contexts.
Construct and optimise predictive models using multiple and nonlinear regression techniques to forecast outcomes and improve decision-making.
Synthesise probability and statistical knowledge to develop innovative solutions for complex analytical challenges.
Compétences que vous acquerrez
Ce que vous apprendrez
Analyse and assess complex problems by applying set theory and functions, ensuring accurate and efficient solutions are developed.
Design and evaluate graph-based models to optimise algorithms and enhance network analysis in cryptography and database management contexts.
Critique mathematical proofs and reasoning to enhance problem-solving skills in varied scenarios.
Innovate discrete structures to efficiently solve problems in data structures, operating systems, and computation theory.
Compétences que vous acquerrez
Ce que vous apprendrez
Analyse and evaluate complex data structures using advanced linear algebra techniques.
Implement sophisticated algorithms and apply advanced techniques to optimise and improve machine learning models.
Synthesise and apply mathematical theories to solve complex real-world problems.
Evaluate and develop innovative solutions using linear programming to address complex challenges in machine learning and AI systems.
Compétences que vous acquerrez
Ce que vous apprendrez
Analyse computational problems to identify appropriate proof techniques and logical reasoning methods that best address their complexities.
Design comprehensive solutions to algorithm development challenges by synthesising and applying principles of propositional and predicate logic.
Evaluate system reliability by conducting model checking using temporal logics, and interpret the results to ensure system correctness.
Construct formal verification plans for algorithms and programs using Floyd-Hoare logics and justify their correctness through logical reasoning.
Compétences que vous acquerrez
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Foire Aux Questions
This Specialization provides a comprehensive mathematical foundation essential for careers in engineering, data science, and artificial intelligence. It's important because strong mathematical skills are consistently cited as critical requirements for technical roles, and mastering these five mathematical domains will significantly enhance your problem-solving capabilities and career prospects.
This Specialization is designed for undergraduate and engineering students, computer science majors, data scientists, AI developers, and professionals seeking to strengthen their mathematical foundation. It's suitable for those with basic mathematical knowledge looking to advance their quantitative skills for technical applications.
Upon completing the Specialization, you will have developed a comprehensive mathematical foundation critical to solve complex engineering problems, design efficient algorithms, build and validate mathematical models, perform statistical analyses, implement machine learning techniques, and apply formal verification methods—skills highly valued across engineering, technology, and data science industries.
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