Master calculus 1 using Python: derivatives and applications
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Unclaimed ProfileMastering calculus is a crucial stepping stone for anyone pursuing careers in data science, machine learning, physics, or quantitative finance. 'Master calculus 1 using Python: derivatives and applications' by Mike X Cohen offers a modern, computational approach to this foundational mathematical discipline. Instead of relying solely on traditional pen-and-paper proofs, this comprehensive course bridges the gap between theoretical calculus and practical Python implementation. Students will explore essential concepts such as mathematical functions, limits, and complex differentiation rules, reinforcing their understanding using Python libraries like SymPy for symbolic mathematics, NumPy for numerical processing, and Matplotlib for rich visual representation. Whether you are a beginner looking to build mathematical intuition from scratch or a programmer aiming to implement calculus-based algorithms in code, this course provides the perfect blend of theory and practice. By the end of the course, you will confidently solve analytical problems by hand and translate those solutions into clean, efficient Python scripts, preparing you for advanced topics in scientific computing and artificial intelligence.
About the creator
Mike X Cohen
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Mike X Cohen is an educator, author, and scientist with over two decades of experience in data science, neuroscience, mathematics, and programming. Formerly an associate professor at Radboud University, Mike has dedicated his career to demystifying complex technical topics for students, researchers, and professionals worldwide. His teaching philosophy is rooted in hands-on, active learning, which is why his courses focus heavily on writing code, solving practical scientific projects, and building intuitive mathematical foundations rather than memorizing formulas. Mike's unique background enables him to bridge the gap between academic rigor and practical software engineering, making complex concepts like deep learning, calculus,…Show more
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Program Overview
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Learning format
Subcategory
Price
Price may change · updated within 1–2 weeks
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What You'll Learn
- Differential calculus
- Mathematical functions (rational, polynomial, transcendantal, trig)
- Limits and tricks for solving limits problems
- Differentiation rules
- Tips and tricks for differentiation
- Python (numpy and sympy)
- Numerical processing
- Applied calculus
- Visualizing math functions (matplotlib)
Best For
- Aspiring data scientists and machine learning engineers seeking to bridge the gap between abstract math and code.
- Computer science students wanting to visualize mathematical concepts using libraries like Matplotlib and SymPy.
- Professionals who need to implement calculus-based algorithms in Python for research or quantitative finance.
- Learners who prefer a modern, computational approach to calculus over traditional manual derivation methods.
Not For
- Pure mathematicians looking for rigorous, theoretical proofs without a focus on programming implementation.
- Learners who have no prior experience with the basics of the Python programming language.
- Students looking for a quick reference guide rather than a deep, 40-hour conceptual masterclass.
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