Coursera

Physics 101 - Rotational Motion and Gravitation (Coursera)

Offered by Rice University,

This course serves as an introduction to the physics of rotational motion and gravitation. Upon completion, learners will have an understanding of how mathematical laws and conservation principles describe the motions and interactions of objects all around us. They will gain experience in solving physics problems with tools such as graphical analysis, algebra, vector analysis, and calculus.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

The course is the third course in the Physics 101 specialization, which follows the typical progression of topics of a first-semester university physics course: Kinematics, Newton’s Laws, Energy, and Momentum. Each of the modules contains reading links to a free textbook, complete video lectures, conceptual quizzes, and a set of homework problems. Once the modules are completed, the course ends with an exam. This comprehensive course is similar in detail and rigor to those taught on-campus. It will thoroughly prepare learners for their upcoming introductory physics courses, or more advanced courses in physics.
What You Will Learn

Learners will be prepared to critically evaluate real-world data and information regarding motion.
Learners can apply mathematical laws to the motions of objects under a variety of physical circumstances.
Learners will be prepared for more advanced courses in physics.

Course 3 of 3 in the Introduction to Mechanics Specialization

Syllabus

WEEK 1: Rotational Motion
WEEK 2: Angular Momentum
WEEK 3: Universal Gravitation
WEEK 4: Rotational Motion and Gravitation EXAM - This module contains the exam that covers Forces and Kinematics. The style is very similar to the homework problems sets, except you must complete it on your own.

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

University of California, Davis

Materials Science: 10 Things Every Engineer Should Know (Coursera)

Engineering Sci: Chemistry

We explore “10 things” that range from the menu of materials available to engineers in their profession to the many mechanical and electrical properties of materials important to their use in various engineering fields. We also discuss the principles behind the manufacturing of those materials. By the end of the course, you will be able to: recognize the important aspects of the materials used in modern engineering applications; explain the underlying principle of materials science: “structure leads to properties,”; identify the role of thermally activated processes in many of these important “things” – as illustrated by the Arrhenius relationship; relate each of these topics to issues that have arisen (or potentially could arise) in your life and work.

Jun 8th 2026

5-12 Weeks

Engineering Semiconductors Materials

Coursera

Princeton University

Analysis of Algorithms (Coursera)

CS: Theory

This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.

Jun 8th 2026

5-12 Weeks

Math Calculus Analysis

Coursera

University of Pennsylvania

Calculus: Single Variable Part 3 - Integration (Coursera)

Sci: Mathematics

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences.

Jun 8th 2026

4 Weeks

Math Calculus Differential Equations

Coursera

University of Maryland, College Park

Framework for Data Collection and Analysis (Coursera)

Statistics & Data Analysis Data Science

This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan.

Jun 8th 2026

4 Weeks

Analysis Data Analysis Analytics

Coursera

Johns Hopkins University

Calculus through Data & Modelling: Series and Integration (Coursera)

Sci: Mathematics

This course continues your study of calculus by introducing the notions of series, sequences, and integration. These foundational tools allow us to develop the theory and applications of the second major tool of calculus: the integral. Rather than measure rates of change, the integral provides a means for measuring the accumulation of a quantity over some interval of input values. This notion of accumulation can be applied to different quantities, including money, populations, weight, area, volume, and air pollutants. The concepts in this course apply to many other disciplines outside of traditional mathematics.

Jun 8th 2026

5-12 Weeks

Calculus Data Sequences

Coursera

University of Pennsylvania

Calculus: Single Variable Part 4 - Applications (Coursera)

Sci: Mathematics

Jun 8th 2026

5-12 Weeks

Math Calculus Probability

Coursera

University of Colorado Boulder

Ideal Gases (Coursera)

Engineering

Course 3 of Statistical Thermodynamics, Ideal Gases, explores the behavior of systems when intermolecular forces are not important. This done by evaluating the appropriate partition functions for translational, rotational, vibrational and/or electronic motion. We start with pure ideal gases including monatomic, diatomic and polyatomic species.

Jun 8th 2026

3 Weeks

Chemistry Thermodynamics Mechanical Engineering

Coursera

IBM

Deep Learning and Reinforcement Learning (Coursera)

Data Science

This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.

Jun 8th 2026

5-12 Weeks

Calculus Python Statistics

Coursera

University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Jun 8th 2026

4 Weeks

Algebra Algorithms Databases

Coursera

University of Colorado Boulder

Quantum Mechanics (Coursera)

Engineering

Course 2 of Statistical Thermodynamics presents an introduction to quantum mechanics at a level appropriate for those with mechanical or aerospace engineering backgrounds. Using a postulatory approach that describes the steps to follow, the Schrodinger wave equation is derived and simple solutions obtained that illustrate atomic and molecular structural behavior. More realistic behavior is also explored along with modern quantum chemistry numerical solution methods for solving the wave equation.

Jun 8th 2026

3 Weeks

Chemistry Thermodynamics Quantum Mechanics

Coursera

École normale supérieure

Introduction à la théorie de Galois (Coursera)

Sci: Mathematics

Le cours expose la théorie de Galois, du classique critère de non-résolubilité des équations polynomiales aux méthodes plus avancées de calcul de groupes de Galois par réduction modulo un nombre premier. Le thème général de cette théorie est l'étude des racines d'un polynôme et concerne en particulier la possibilité de les exprimer à partir des coefficients de ce polynôme. Evariste Galois considère les symétries de ces racines et associe ainsi à ce polynôme un groupe de permutations de ses racines, que l'on appelle maintenant son groupe de Galois.

Jun 8th 2026

5-12 Weeks

Math Algebra Galois Theory

Coursera

École Polytechnique

Fundamentals of waves and vibrations (Coursera)

Engineering Sci: Physics

Waves are everywhere. On water of course, but also in the air as you hear a plane, and under your feet during an earthquake certainly. Vibrations, too, are everywhere In your bike as you go over a bump, in you guitar as you play, and of course in your smartphone. You can guess that there is something in common behind all this. This is exactly the purpose of this course !

Jun 8th 2026

5-12 Weeks

Mechanics Mechanical Engineering Vibrations