What you will learn
- Gain a deep understanding of linear algebra, including vectors, matrices, and transformations.
- Learn multivariable calculus concepts essential for optimization in machine learning.
- Explore probability and statistics to analyze data and make informed decisions.
- Develop skills in mathematical modeling for real-world AI and machine learning applications.
- Apply mathematical techniques to practical machine learning problems.
- Work on hands-on exercises and projects to solidify learning.
Program Overview
Linear Algebra for Machine Learning
⏱️ 4-6 weeks
- Understand vectors, matrices, and operations used in ML.
- Learn about eigenvalues, eigenvectors, and their applications.
- Explore transformations and their impact on machine learning algorithms.
Multivariable Calculus for Machine Learning
⏱️6-8 weeks
- Learn differentiation and gradient-based optimization.
- Explore partial derivatives and their role in neural networks.
- Understand backpropagation in deep learning models.
Probability and Statistics for Machine Learning
⏱️6-10 weeks
- Learn probability distributions, Bayes’ theorem, and statistical inference.
- Understand hypothesis testing and confidence intervals for data-driven decision-making.
- Explore Markov Chains and their applications in machine learning.
Capstone Project: Applying Mathematics to Machine Learning
⏱️8-12 weeks
- Work on real-world applications integrating linear algebra, calculus, and probability.
- Apply mathematical techniques to optimize ML models.
- Gain practical experience through case studies and coding exercises.
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Job Outlook
- High Demand for ML Engineers: Companies seek professionals with a strong mathematical foundation for AI and ML development.
- Competitive Salaries: Machine learning engineers earn $100,000 – $150,000+, with higher pay for expertise in mathematics-driven AI.
- Versatile Applications: Math skills are crucial for AI, finance, robotics, and data science roles.
- Industry Recognition: A strong math background is essential for advanced AI and deep learning careers.
- Career Pathways: Ideal for roles in machine learning, AI research, quantitative analysis, and data science.
Specification: Mathematics for Machine Learning Specialization
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