Online Pre-College Programs and Courses

This online course introduces students to important concepts in data analytics across a wide range of case studies. Students will learn how to gather, analyze, and interpret data to drive strategic and operational success. They’ll explore how to clean and organize data for analysis and how to perform calculations using spreadsheets, SQL and R programming. Topics include the data science lifecycle, probability, statistics, hypothesis testing, set theory, graphing, regression, and data ethics.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course is designed to develop students' understanding of fundamental concepts of financial mathematics.  The course will cover mathematical theory and applications including the time value of money, annuities and cash flows, bond pricing, loans, amortization, stock and portfolio pricing, immunization of portfolios, swaps and determinants of interest rates, asset matching and convexity.  A basic knowledge of calculus and an introductory knowledge of probability is assumed.

Prerequisite: Calculus I or equivalent.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

An Introduction to Mathematical Cryptography is an introduction to modern cryptography with an emphasis on the mathematics behind the theory of public key cryptosystems and digital signature schemes. The course develops the mathematical tools needed for the construction and security analysis of diverse cryptosystems. Other topics central to mathematical cryptography covered are: classical cryptographic constructions, such as Diffie-Hellmann key exchange, discrete logarithm-based cryptosystems, the RSA cryptosystem, and digital signatures. Fundamental mathematical tools for cryptography studied include: primality testing, factorization algorithms, probability theory, information theory, and collision algorithms. A survey of important recent cryptographic innovations, such as elliptic curves, elliptic curve and pairing-based cryptography are included as well. This course is an ideal introduction for mathematics and computer science students to the mathematical foundations of modern cryptography.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course follows the actuarial Exam P syllabus and learning objectives to prepare students to pass the SOA/CAS Probability Exam. Topics include axioms of probability, discrete and continuous random variables, conditional probability, Bayes’ theorem, Chebyshev's Theorem, Central Limit Theorem, univariate and joint distributions and expectations, loss frequency, loss severity and other risk management concepts. Exam P learning objectives and learning outcomes are emphasized.

Prerequisite: Calculus II.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course will provide a practical introduction to mathematical proofs with the aim of developing fluency in the language of mathematics, which itself is often described as “the language of the universe.” Along with a library of proof techniques, we shall tour propositional logic, set theory, cardinal arithmetic, and metric topology and explore “proof relevant” mathematics by interacting with a computer proof assistant. This course on the construction of mathematical proof will conclude with a deconstruction of mathematical proof, interrogating the extent to which proof serves as a means to discover universal truths and assessing the mechanisms by which the mathematical community achieves consensus regarding whether a claimed result has been proven.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

Topological spaces, connectedness, compactness, quotient spaces, metric spaces, function spaces. An introduction to algebraic topology: covering spaces, the fundamental group, and other topics as time permits.

Prerequisite: AS.110.202 (Calculus III) or AS.110.211 (Honors Multivariable Calculus).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

Vector spaces, matrices, and linear transformations. Solutions of systems of linear equations. Eigenvalues, eigenvectors, and diagonalization of matrices. Applications to differential equations.

Prerequisite: Grade of C- or better in AS.110.107 (Calculus II For Biological and Social Science) or AS.110.109 (Calculus II For Physical Sciences and Engineering) or AS.110.113 (Honors Single Variable Calculus) or AS.110.202 (Calculus II) or AS.110.302 (Differential Equaitions and Applications), or a 5 on the AP BC exam.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course is designed for students of all backgrounds to provide a solid foundation in the underlying mathematical, programming, and statistical theory of data analysis. In today's data driven world, data literacy is an increasingly important skill to master. To this end, the course will motivate the fundamental concepts used in this growing field. While discussing the general theory behind common methods of data science there will be numerous applications to real world data sets. In particular, the course will use Python libraries to create, import, and analyze data sets. 

Prerequisites: There are no mathematical prerequisites for this course although prior knowledge of calculus, statistics and/or programming can be helpful.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course is an introduction to the theory of functions of one complex variable. Its emphasis is on techniques and applications, and it serves as a basis for more advanced courses. Functions of a complex variable and their derivatives; power series and Laurent expansions; Cauchy integral theorem and formula; calculus of residues and contour integrals; harmonic functions.

Prerequisite: Grade of C- or better in AS.110.202 (Calculus III) or AS.110.211 (Honors Multivariable Calculus).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

Is the mind identical to the brain? Is the mind (or brain) a computer? Could a computer reason, have emotions, or be ethically culpable? How have computers changed our minds? This course examines such questions philosophically and historically. Topics include early AI research, computationalism, connectionism, 4EA cognitive science, simulation theory, and the Singularity.

This online course is primarily delivered asynchronously; however, students will be expected to attend a 90-minue online discussion session once per week at a mutually agreed upon time. Your instructor may schedule additional live interactions as well. Please refer to your syllabus for these opportunities and for important course deadlines.

Population genomics is the study of the structure, function, and variability of the entire genetic complement of organisms considered on a population scale. By examining how gene variants change in structure and frequency in populations over time, we can study the process of evolution and how it contributes to biodiversity and the formation of new species; this information can be used to increase the efficacy of conservation efforts. By studying gene variants underlying diseases at the scale of populations, we can better diagnose complex polygenic diseases like cancer. This course introduces the fundamentals of population genomics and provides an overview of the subfields of evolutionary genomics, conservation genomics, and medical genomics.

This self-paced program is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for your important program deadlines.

Prerequisite: At least one semester of high school biology is recommened, but not required.

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

Population genomics is the study of the structure, function, and variability of the entire genetic complement of organisms considered on a population scale. By examining how gene variants change in structure and frequency in populations over time, we can study the process of evolution and how it contributes to biodiversity and the formation of new species; this information can be used to increase the efficacy of conservation efforts. By studying gene variants underlying diseases at the scale of populations, we can better diagnose complex polygenic diseases like cancer. This course introduces the fundamentals of population genomics and provides an overview of the subfields of evolutionary genomics, conservation genomics, and medical genomics.

This self-paced program is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for your important program deadlines.

Prerequisite: At least one semester of high school biology is recommened, but not required.

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

Population genomics is the study of the structure, function, and variability of the entire genetic complement of organisms considered on a population scale. By examining how gene variants change in structure and frequency in populations over time, we can study the process of evolution and how it contributes to biodiversity and the formation of new species; this information can be used to increase the efficacy of conservation efforts. By studying gene variants underlying diseases at the scale of populations, we can better diagnose complex polygenic diseases like cancer. This course introduces the fundamentals of population genomics and provides an overview of the subfields of evolutionary genomics, conservation genomics, and medical genomics.

This self-paced program is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for your important program deadlines.

Prerequisite: At least one semester of high school biology is recommened, but not required.

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

This course starts from scratch and provides students with all the background necessary for the study of calculus. It includes a review of algebra, trigonometry, exponential and logarithmic functions, coordinates and graphs. Each of these tools will be introduced in its cultural and historical context. The concept of the rate of change of a function will be introduced. Not open to students who have studied calculus in high school.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course is designed to give a firm grounding in the basic tools of analysis. It is recommended as preparation (but may not be a prerequisite) for other advanced analysis courses and may be taken as an Introduction to Proofs (IP) course. Topics include the formal properties of real and complex number systems, topology of metric spaces, limits, continuity, infinite sequences and series, differentiation, Riemann-Stieltjes integration. 

Prerequisite: Grade of C- or better in AS.110.201 (Linear Algebra) or AS.110.212 (Honors Linear Algebra), AND 110.202 (Calculus III) or 110.211 (Honors Multivariable Calculus).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course continues AS.110.405 (Real Analysis I) with an emphasis on the fundamental notions of modern analysis. Sequences and series of functions, Fourier series, equicontinuity and the Arzela-Ascoli theorem, the Stone-Weierstrass theorem, functions of several variables, the inverse and implicit function theorems, introduction to the Lebesgue integral.

Prerequisite: AS.110.405 (Real Anaylsis I) or AS.110.415 (Honors Analysis I).

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

This course is designed for students of all backgrounds to provide a mathematical introduction social choice theory, weighted voting systems, apportionment methods, and gerrymandering. In the search for ideal ways to make certain kinds of political decisions, a lot of wasted effort could be averted if mathematics could determine that finding such an ideal were actually possible in the first place. The course will analyze data from recent US elections as well as provide historical context to modern discussions in politics, culminating in a mathematical analysis of the US Electoral College. Case studies, future implications, and comparisons to other governing bodies outside the US are used to apply the theory of the course. Students will use Microsoft Excel to analyze data sets. There are no mathematical prerequisites for this course.

A flexible weekly schedule accommodates all student schedules and time zones, and courses include pre-recorded lectures, notes, and interactives to help students learn the material. Assessments include computer-scored items for immediate feedback as well as instructor-graded assignments for personalized learning. Students have access to instructors through email or individual reviews, and weekly instructor-led synchronous problem-solving sessions are recorded to view any time. Students should expect to work a minimum of 5-10 hours per week.

A writing-intensive (W) course is one in which students complete at least 20 pages of finished writing, distributed over multiple assignments, usually 3 or 4 papers, throughout the term. For Johns Hopkins University undergraduates, The Mathematics of Politics, Democracy, and Social Choice counts towards the 12 required credit hours of writing-intensive courses.