Please find a list of courses I have taken during my academic period.
New York University
Masters of Science in Computer Science
Degree Conferred: May 2023
Fall 2021
• Fundamental Algorithms – CSCI-GA 1170
Reviews a number of important algorithms, with emphasis on correctness and efficiency. The topics covered include solution of recurrence equations, sorting algorithms, selection, binary search trees and balanced-tree strategies, tree traversal, partitioning, graphs, spanning trees, shortest paths, connectivity, depth-first and breadth-first search, dynamic programming, and divide-and-conquer techniques.
• Programming Languages – CSCI-GA 2110
Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.
• Database Systems – CSCI-GA 2433
Database system architecture. Modeling an application and logical database design. The relational model and relational data definition and data manipulation languages. Design of relational databases and normalization theory. Physical database design. Concurrency and recovery. Query processing and optimization.
Spring 2022
• Operating Systems – CSCI-GA 2250
The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows.
• Special Topics in Computer Science: Social Networks – CSCI-GA 3033
This course will introduce the tools for the study of networks, and mechanism designed to interact strategically: SmartContractss, Costly Signaling, Credible and Noncredible Threats, Model Checking and Verification, Safety and Liveness, Recommenders and Verifiers, Deception, Market mechanisms (pricing and auction), Privacy and Trust
• Data Analytics and Visualization in Healthcare – CSCI-GA 3033
This course provides foundational knowledge of data analytics and visualization applied to healthcare settings. Some topics include Health Information Technology (HIT) systems and components, use of R and Python programming languages for data analytics and visualization, best practices in data visualization, design of dashboards using Tableau, and descriptive and predictive analytics methods for healthcare.
Summer 2022
• Internship in Computer Science – OneReach.ai
Provides an in-depth understanding of designing conversational AI solutions using advanced platforms like Communication Studio. Developled rich web chat, SMS, and IVR bots, integrate APIs, and create user-centric workflows for seamless interactions. Topics include bot design principles, Slack API integration, ticket management systems, and addressing social challenges through AI-driven solutions. Through collaborative projects, enhance their technical skills in conversational AI while focusing on design, usability, and impactful applications in real-world scenarios
Fall 2022
• DevOps and Agile Methodologies – CSCI-GA 2820
This course uses a project based learning approach towards the study of DevOps as a cultural change in Information Technology organizations, and the supporting development tools and automation technologies required to implement it successfully. Students study the principles of DevOps, and as part of an agile development team, each student is involved in planning, designing, building, testing, and deploying one or more cloud native microservices into a Platform as a Service cloud by utilizing a DevOps Pipeline that they will create.
• Special Topics in Computer Science: Cloud and Machine Learning – CSCI-GA 3033
This course exposes students to the practical aspects of the state of art in cloud computing with an emphasis on employing cloud for machine learning problems. The course material introduces students to various cloud technologies such as virtualization and container. Students will learn how to build machine learning systems using cloud computing, the application performance characteristics, and develop hands-on experience with programming machine learning applications on the cloud platforms.
• Internship in Computer Science – Glocol Networks
Explored the deployment and management of IoT devices for real-time monitoring and analytics in public transit systems. Calibrated IoT-based occupancy detection systems, optimize data processing pipelines, and build cloud-hosted dashboards for visualization and control. Included hands-on experience with AWS Greengrass, Grafana, and data visualization tools, focusing on solving urban mobility challenges and real-time analytics for informed decision-making in transportation systems.
Spring 2023
• Responsible Data Science – DS-GA 1017
As we develop and deploy data science methods, we are compelled to think about the effects these methods have on individuals, population groups, and on society at large. Responsible Data Science is a technical course that tackles the issues of ethics, legal compliance, data quality, algorithmic fairness and diversity, transparency of data and algorithms, privacy, and data protection.
• Data Science for Business: Technical – TECH-GB 2336
We will examine how data analytics and machine learning can be used to improve decision-making. We will study the fundamental principles and techniques of data science, machine learning, and data-driven artificial intelligence, and we will examine real-world examples and cases to place data science techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much art as science.
Summer 2021
• Internship in Computer Science – Axians
Worked with Axians’ Location Intelligence Team to use algorithms and satellite images to determine whether infrastructure projects are advancing at an appropriate pace without needing to send people to the locations themselves. This will involve using pixel-based classification machine learning to identify and monitor power lines, geographical features, obstructions and other changes in the landscape.
University of San Francisco
Bachelor of Science in Computer Science, Economics
Degree Conferred: May 2021
Fall 2017
• General Chemistry I – CHEM 111
The first in a two-semester course sequence, this course introduces the fundamental principles of modern chemistry, including atomic and molecular structure, periodicity of the elements, stoichiometry, properties of gases and of solutions.
• Laboratory – CHEM 112
A laboratory course designed to accompany General Chemistry I. Emphasis is placed on experiments that illustrate the fundamental principles and laws of chemical behavior and engage students in cooperative data acquisition and analysis. Topics include accuracy/precision, qualitative analysis, titrations, atomic spectroscopy, properties of gases and of solutions. Assessment based on laboratory technique, pre-lab assignments, written laboratory reports, accuracy of analyses, and a final exam.
• Intro to Computer Science I (Python) – CS 110
Use of procedures, parameter passing, block structures, data types, arrays, abstract data structures, conditional control, iterative and recursive processes, and input/output in programming solutions to a variety of problems. Top-down and bottom-up design and functional decomposition to aid in the development of programs.
• Calculus & Analytic Geometry I – MATH 109
Differentiation of algebraic, exponential, logarithmic, trigonometric, and inverse trigonometric functions; implicit differentiation; curve sketching; indeterminate forms; velocity and acceleration; optimization; other applications of differentiation; Fundamental Theorem of Calculus, with applications to area and volume.
• Written & Oral Communication – RHET 130
In the first semester, students learn the basic practices of oral and written argument by writing a minimum of 7000 words of revised prose in essays of increasing length and complexity, including one research paper, and by giving two prepared speeches. Students learn to use textual support for argument, to read critically, to use transitions and documentation, and to organize appeals in support of a claim. They learn methods of development, practice and delivery for a variety of speeches, including topic selection, speech outlines, audience analysis, and visual aids.
Spring 2018
• Intro to Computer Science II (Java) – CS 112
Design and development of significantly sized software using top-down design and bottom-up implementation. Dynamically allocated data, object-oriented programming, architecture of memory, basics of language translation, and basics of algorithm analysis. Development of simple graphical user interfaces.
• Discrete Mathematics – MATH 201
Topics include algebraic structures, graph theory, combinatorics, and symbolic logic.
• FYS: Minds and Machines – PHIL 195
You spend your entire life inside your own head. There is nothing that you know more intimately than the contents of your own mind: your beliefs, your memories, your desires, your fears, your pains and pleasures. Despite the fact that you are directly acquainted with your thoughts and experiences, the human mind is in many ways more mysterious than even the far reaches of the universe. In this course, we will investigate the nature of the mind, and the relationship between the mind, the brain, and the body. We will also critically examine some of the ethical and social implications of artificial intelligence.
• Written & Oral Communication – RHET 131
In the second semester, students expand their skills of argumentation and style, writing a minimum of 9000 words of revised prose and giving a minimum of two speeches: written and oral arguments of fact, value and policy, including research.
Fall 2018
• C and Systems Programming – CS 221
Introduction to the C programming language and UNIX/Linux systems programming. Pointers in C, libraries, devices, processes, threads, system calls, memory management, and interprocess communication with sockets.
• Data Structures & Algorithms – CS 245
Algorithm analysis and asymptotic running time calculations. Algorithm design techniques and implementation details. Algorithms for sorting and searching, trees, graphs, and other selected topics.
• Modern African History – HIST 150
This course introduces students to the diverse history of Africa from 1450 to the present. Topics examined include the development of African societies and political systems, internal and external slave trades, African societies and politics, African resistance to foreign rule, European colonization, nationalist struggles for independence, and legacies of colonial rule.
• Elementary Statistics – MATH 101
This course will introduce students to the processes by which valid statistical inferences may be drawn from quantitative data. Topics include design of experiments; sample surveys; measurement; summary and presentation of data; regression and correlation; elementary probability; the law of averages; the central limit theorem; the normal, t and chi-square distributions; confidence intervals; and hypothesis testing.
Spring 2019
• Software Development – CS 212
Advanced programming topics including inheritance and polymorphism, multi-threaded programming, networking, database programming, and web development. Techniques for debugging, refactoring, and reviewing code.
• Intermediate Macroeconomics – ECON 312
Analysis of national income determination; function of money and commercial banking; methods and objectives of fiscal policy.
• Linear Algebra & Probability – MATH 202
Matrix arithmetric and matrix algebra (determinants, adding and multiplying matrices, matrix inverse, using matrices to solve systems of equations), geometric applications of linear algebra (matrices as transformations, vectors in 2- and 3-dimensions, equations of planes, etc.); discrete probability, random variables, discrete and continuous probability distributions (including binomial and normal), expected value and variance.
• Ethics – PHIL 240
This course critically analyzes ethical arguments and various positions on contemporary ethical issues. The course will be composed of three focus areas: Ethical Theory, Social Issues, and Ethics of Everyday life. Approximately one-third of the course will be devoted to each area. Some sections focus on more specific ethical issues, such as Business Issues, Environmental Issues, Bio-medical Issues, and Legal Issues.
Fall 2019
• Computer Architecture – CS 315
Performance analysis techniques, instruction set design, computer arithmetic, digital design, processor implementation, and memory systems. Performance enhancement using pipelining and cache memory.
• Special Topics: Blockchain – CS 486
Blockchain is a distributed data structure with special properties, such as tamper-resistance, which has gained interest worldwide as a backbone of cryptocurrency. This course covers public-key cryptography, one-way hash functions, Merkle tree, proof-of-work, proof-of-stake, Byzantine-fault tolerance and consensus algorithms, so that you can understand the mechanisms of blockchain.
• Special Topics: Career Prep – CS 486
This course will help prepare students to start a Software Engineer career. The focus will be on technical interviewing. This will be a hands-on course where you will be solving whiteboard challenges and common coding interview questions. We’ll also discuss the entire job search process, including (but not limited to) improving your resume and online portfolio, how to network, negotiating compensation packages, being successful on the job, and networking with alumni.
• Jews, Judaisms & Jewish Identity – THRS 130
As individuals and communities, we enact identities (or constructed senses of self) through our behavior and experiences. Shaped by cultures, value systems, histories, and narratives, our identities relate to virtually every aspect of our lives. This class explores this central part of being human, using “Jews” as an entry point. In this course, we ask, “What does it mean to be a Jew in the 21st century?” to figure out students’ own social identities. We look at how Jews have reshaped their customs, practices, and beliefs over centuries, weaving together dominant and marginalized voices along the way.
• Acting Foundations – THTR 110
This experiential course introduces students to the history, theory and practices of the craft of acting. Students will learn techniques for analyzing and preparing dramatic texts, and put them into practice through class exercises and scene assignments. Throughout the course, students will engage in a variety of practical exercises geared toward expanding the expressive potential of their voices, bodies and imaginations.
Spring 2020
• Cultures in Conflict – CMPL 200
A substantial introduction to the basic principles and methodology of literary analysis for comparing works of different cultural origins, time periods, and regions of the world. This course will focus on representations of conflicts in literature that sustain a diversity of perspectives including issues of war, power, class, gender and ethnicity, displacement and discrimination.
• Special Topics: Introduction to Tableau – CS 186
Opportunities to learn the many features available in Tableau and work with datasets, visualizations, reports, and dashboards. Students will practice connecting to data sources, working with dimensions and measures, developing reports and charts, saving workbooks, filtering, swapping, sorting, formatting, grouping, creating hierarchies, forecasting, exporting, distributing, as well developing various chart types.
• Operating Systems – CS 326
The design and implementation of operating systems. Study of processes, threads, scheduling, synchronization, interprocess communication, device drivers, memory management, and file systems.
• Data Visualization – CS 360
This course introduces both undergraduate and graduate students to the fundamentals of data visualization. This includes discussion of perception, design, and evaluation. Students will also be introduced to a variety of visualization techniques for high-dimensional, temporal, hierarchical, network, and/or geospatial data.
• Econometrics – ECON 320
This course prepares the student in the use of econometric techniques, such as linear regression, hypothesis testing, and model-building. The focus is on the application of econometrics to applied problems in finance, macroeconomics, development, and international economics.
Summer 2020
• Intermediate Microeconomics – ECON 311
Course examines the choices and decisions of consumers and firms in the context of full information, uncertainty, and imperfect information.
Fall 2020
• Creating Images: Photoshop I – CS 131
Introduction to image design, manipulation and processing for utilization in print, on the web and photographically. Acquiring images through scanning, from the Web and other sources. Introduction to Adobe Photoshop tools and palettes. Use of Photoshop tool in image correction, development and collaging. Students develop a portfolio of images.
• Special Topics: Machine Learning – CS 486
A broad introduction to machine learning and pattern recognition. Topics include regression, classification, clustering and dimensionality reduction.
• Senior Team Project – CS 490
Students working in teams investigate, specify, design, implement, test, document, and present to their classmates a significant software project. Sound software engineering practices are presented in lectures and used to evaluate each stage of the project. Written and verbal communication is emphasized through frequent documentation submissions, informal group discussions, code walk-throughs, and student presentations.
• Money, Banking/Financial Institutions – ECON 350
This course investigates the changing role of financial institutions, financial markets, and monetary policy in a modern economy. The focus is on how monetary policy influences macroeconomic variables and financial institutions and markets.
• Econometrics of Financial Markets – ECON 425
This course introduces students to the econometric theory and techniques most useful in examining and testing models common in finance and macro-economics. This includes such topics as forecasting prices and returns of financial instruments, testing hypotheses regarding market efficiency and arbitrage, and modeling the time-series nature of financial market data.
Spring 2021
• Intro to AI – CS 462
This course provides students with an introduction to the foundational ideas and approaches to artificial intelligence, including search, knowledge representation and learning, along with contextual knowledge about ethics and social impact.
• Fundamentals of Macro Data – ECON 324
This course teaches how to obtain, understand, and use macroeconomic and financial data for analysis and forecasting. Students learn about macroeconomic indicators measuring growth, inflation, unemployment, housing prices, and other important economic variables.
• Applied Econometrics Capstone – ECON 427
Introduces more advanced econometrics topics and guides students to synthesize material from their Economics major to research and write a senior thesis. Topics include binary dependent variables, analysis of panel data, instrumental variables estimation, treatment effects estimation, quantile regression, and nonparametric estimation.
• Community Garden Outreach – ENVA 245
Explored food security issues through semester-long Service Learning internships with organizations involved in the production, use, distribution and/or promotion of locally grown organic produce.
• Special Topics: Intro to Data Ethics – HONC 390
Discussion of issues related to global humanities.