Birla Institute of Technology & Science, Pilani
Mathematics for Engineering Specialization
Birla Institute of Technology & Science, Pilani

Mathematics for Engineering Specialization

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

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Beginner level

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4 months at 10 hours a week
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Get in-depth knowledge of a subject
Beginner level

Recommended experience

4 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • 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.

Overview

What’s included

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Taught in English
Recently updated!

August 2025

502 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Birla Institute of Technology & Science, Pilani

Specialization - 5 course series

What you'll learn

  • 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.

Skills you'll gain

Engineering Calculations, Mathematical Theory & Analysis, Engineering Analysis, Calculus, Differential Equations, Algebra, Integral Calculus, Geometry, Linear Algebra, Mathematical Modeling, Advanced Mathematics, Applied Mathematics, Derivatives, and Trigonometry

What you'll learn

  • 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.

Skills you'll gain

Data Analysis, Applied Mathematics, Analytics, Data Visualization, Statistical Analysis, Predictive Modeling, and Statistical Modeling

What you'll learn

  • 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.

Skills you'll gain

Algorithms, Theoretical Computer Science, Applied Mathematics, Programming Principles, Cryptography, Probability & Statistics, and Data Management

What you'll learn

  • 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.

Skills you'll gain

Data Analysis, Machine Learning, Linear Algebra, Artificial Neural Networks, Dimensionality Reduction, Applied Mathematics, Numerical Analysis, and Artificial Intelligence and Machine Learning (AI/ML)

What you'll learn

  • 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.

Skills you'll gain

Computational Logic, Verification And Validation, Algorithms, Logical Reasoning, Deductive Reasoning, Computer Programming, Analytical Skills, Program Development, Computational Thinking, Software Development, Data Analysis, Machine Learning, Computer Science, and Theoretical Computer Science

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Instructor

BITS Pilani Instructors Group
Birla Institute of Technology & Science, Pilani
14 Courses38,683 learners

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