Calculus 1, part 2 of 2: Derivatives with applications

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课程名称:微积分 1,第 2 部分:导数及其应用 课程概述: 本课程是微积分的第二部分,主要集中在单变量微积分中的导数及其应用。通过课程的学习,您将全面了解导数的概念及其重要性,掌握导数的定义和基本计算;深入学习常见函数的导数推导,包括常数函数、单项式、三角函数、指数函数和对数函数等。此外,您还将学习链式法则、逆函数的导数意义,以及重要的均值定理和其他相关理论。 课程内容: 1. **课程介绍**:了解课程内容及微分微积分的重要性。 2. **导数的定义与实例**:学习导数的正式定义,几何解释及导数计算。 3. **基本函数的导数推导**:学习常见基本函数的导数公式及其运用。 4. **链式法则与相关速率**:理解复合函数的导数计算以及相关速率问题的解决方法。 5. **逆函数的导数**:介绍可微逆函数的导数公式及其几何直观。 6. **均值定理及其他重要定理**:学习均值定理及其应用,理解关键点和极值的相关概念。 7. **应用:单调性与优化**:应用导数分析函数的单调性和优化问题。 8. **凹凸性与二阶导数**:通过二阶导数判断函数的凹凸性与拐点。 9. **洛必达法则及应用**:学习如何使用洛必达法则求解不定型极限。 10. **高阶导数与泰勒公式初探**:了解高阶导数的概念及泰勒多项式的基础知识。 11. **隐式求导**:学习如何通过隐式关系推导导数。 12. **对数微分**:掌握对数微分的应用及适用情况。 13. **偏导数简介**:对多变量函数的偏导数进行初步了解。 14. **不定积分简介**:了解积分的应用及主要积分技巧。 15. **常微分方程简介**:学习常微分方程的一些基础知识。 16. **建立在导数概念上的高级概念**:探讨偏导数、梯度、雅可比、海森矩阵等更高级的导数概念。 17. **问题解决:优化**:通过实践解决优化问题。 18. **问题解决:函数绘图**:学习如何制作函数及其导数的变化表,并练习函数绘图。 课程还提供了详细的学习资源,包括245个视频和330个解决问题的文本资料,以帮助您更好地理解和掌握微积分的应用。完成课程后,请与您的教授确认考试所需内容。

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Calculus 1, part 2 of 2: Derivatives with applicationsSingle variable calculusS1. Introduction to the courseYou will learn: about the content of this course and about importance of Differential Calculus. The purpose of this section is not to teach you all the details (this comes later in the course) but to show you the big picture.S2. Definition of the derivative, with some examples and illustrationsYou will learn: the formal definition of derivatives and differentiability; terminology and notation; geometrical interpretation of derivative at a point; tangent lines and their equations; how to compute some derivatives directly from the definition and see the result it gives together with the graph of the function in the coordinate system; continuity versus differentiability; higher order derivatives; differentials and their geometrical interpretation; linearization.S3. Deriving the derivatives of elementary functionsYou will learn: how to derive the formulas for derivatives of basic elementary functions: the constant function, monic monomials, roots, trigonometric and inverse trigonometric functions, exponential functions, logarithmic functions, and some power functions (more to come in the next section); how to prove and apply the Sum Rule, the Scaling Rule, the Product Rule, and the Quotient Rule for derivatives, and how to use these rules for differentiating plenty of new elementary functions formed from the basic ones; differentiability of continuous piecewise functions defined with help of the elementary ones.S4. The Chain Rule and related ratesYou will learn: how to compute derivatives of composite functions using the Chain Rule; some illustrations and a proof of the Chain Rule; derivations of the formulas for the derivatives of a more general variant of power functions, and of exponential functions with the basis different than e; how to solve some types of problems concerning related rates (the ones that can be solved with help of the Chain Rule).S5. Derivatives of inverse functionsYou will learn: the formula for the derivative of an inverse function to a differentiable invertible function defined on an interval (with a very nice geometrical/trigonometrical intuition behind it); we will revisit some formulas that have been derived earlier in the course and we will show how they can be motivated with help of the new theorem, but you will also see some other examples of application of this theorem.S6. Mean value theorems and other important theoremsYou will learn: various theorems that play an important role for further applications: Mean Value Theorems (Lagrange, Cauchy), Darboux property, Rolle's Theorem, Fermat's Theorem; you will learn their formulations, proofs, intuitive/geometrical interpretations, examples of applications, importance of various assumptions; you will learn some new terms like CP (critical point, a.k.a. stationary point) and singular point; the definitions of local/relative maximum/minimum and global/absolute maximum/minimum will be repeated from Precalculus 1, so that we can use them in the context of Calculus (they will be discussed in a more practical way in Sections 7, 17, and 18).S7. Applications: monotonicity and optimisationYou will learn: how to apply the results from the previous section in more practical settings like examining monotonicity of differentiable functions and optimising (mainly continuous) functions; The First Derivative Test and The Second Derivative Test for classifications of CP (critical points) of differentiable functions.S8. Convexity and second derivativesYou will learn: how to determine with help of the second derivative whether a function is concave of convex on an interval; inflection points and how they look on graphs of functions; the concept of convexity is a general concept, but here we will only apply it to twice differentiable functions.S9. l'Hôpital's rule with applicationsYou will learn: use l'Hôpital's rule for computing the limits of indeterminate forms; you get a very detailed proof in an article attached to the first video in this section.S10. Higher order derivatives and an intro to Taylor's formulaYou will learn: about classes of real-valued functions of a single real variable: C^0, C^1,., C^∞ and some prominent members of these classes; the importance of Taylor/Maclaurin polynomials and their shape for the exponential function, for the sine and for the cosine; you only get a glimpse into these topics, as they are usually a part of Calculus 2.S11. Implicit differentiationYou will learn: how to find the derivative y'(x) from an implicit relation F(x,y)=0 by combining various rules for differentiation; you will get some examples of curves described by implicit relations, but their study is not included in this course (it is usually studied in "Algebraic Geometry", "Differential Geometry" or "Geometry and Topology"; the topic is also partially covered in "Calculus 3 (Multivariable Calculus), part 1 of 2": Implicit Function Theorem).S12. Logarithmic differentiationYou will learn: how to perform logarithmic differentiation and in what type of cases it is practical to apply.S13. Very briefly about partial derivativesYou will learn: how to compute partial derivatives to multivariable functions (just an introduction).S14. Very briefly about antiderivativesYou will learn: about the wonderful applicability of integrals and about the main integration techniques.S15. A very brief introduction to the topic of ODEYou will learn: some very basic stuff about ordinary differential equations.S16. More advanced concepts built upon the concept of derivativeYou will learn: about some more advanced concepts based on the concept of derivative: partial derivative, gradient, jacobian, hessian, derivative of vector-valued functions, divergence, rotation (curl).S17. Problem solving: optimisationYou will learn: how to solve optimisation problems (practice to Section 7).S18. Problem solving: plotting functionsYou will learn: how to make the table of (sign) variations for the function and its derivatives; you get a lot of practice in plotting functions (topic covered partly in "Calculus 1, part 1 of 2: Limits and continuity", and completed in Sections 6-8 of the present course).Make sure that you check with your professor what parts of the course you will need for your final exam. Such things vary from country to country, from university to university, and they can even vary from year to year at the same university.A detailed description of the content of the course, with all the 245 videos and their titles, and with the texts of all the 330 problems solved during this course, is presented in the resource file "001 List_of_all_Videos_and_Problems_Calculus_1_p2.pdf" under video 1 ("Introduction to the course"). This content is also presented in video 1.

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