Double Major in Entrepreneurship (BA) and Computer Science (BSc)

Entrepreneurship Courses

• Entrepreneurship Creativity, Innovation From 0 to 1

  Dr. Tali Ramon / Prof. Tamar Almor

  The course offers students a framework for starting their exploratory journey into the world of entrepreneurship through interactive class discussion and guest lectures. The goal of the course is to acquaint students with the terminology, processes and players in the entrepreneurial eco-system as well as to expose them to various domains in entrepreneurship. The topics that will be covered involve different aspects and challenges of entrepreneurship, idea development and validation, strategy, building a business plan, raising capital and growing a business.
• Research Methods for Entrepreneurs

  Lecturer: Jeffrey Lozon

  The course aims to introduce the principles, rationale, approaches, and methods of empirical and theoretical research in the social sciences, focusing on the business and entrepreneurship context. Topics include the fundamentals of the scientific method, inquiry and hypothesis, ethics, validity and reliability, the range of research methods, and types of research. In class exercises will be carried out in order to apply the learned material and skills.
• Innovation and Intrapeneruship Within Organizations

  lecturer: Dr. Michal Ben David

  The course focuses on both the barriers and enablers that constrain or facilitate innovation. It does so by giving students the opportunity to practice creative thinking, trend forecasting, strategy formulation, and team management using real organizational problems. This course enables students to identify and practice ways of lifting barriers to unleash innovation and sustain it through individual and team effort and organizational culture. Participants will learn about the antecedents to individual and group creativity, how to construct and manage innovation teams, how to identify innovation constraints in organizational and team cultures, and how to implement new and useful ideas across the organization. Learning is both theoretical and experiential – whatever we learn, we will also implement!)
• Applied Tools for Entrepreneurs - A +B

  Lecturers: Dr. Michelle Stein Teer,, Liat Erel, Adv.Eyal Farkash, Lisa Law and Shay Thieberg, Omri Avisa

  This course equips aspiring entrepreneurs with essential tools and strategies to navigate the unique challenges of entrepreneurship. Delivered across two semesters, each semester consists of three focused modules, covering topics including time management, resilience, public speaking, personal branding, networking, ethics, and Excel. Within each module, students will attend diverse lectures designed to enhance their adaptability, productivity, and professionalism, ensuring they are prepared for success in the fast-paced and often unpredictable world of entrepreneurship.

Computer Science Courses

• Linear Algebra I

  Systems of linear equations, Gaussian elimination; Matrices, matrix operations, invertible matrices, a method for inverting matrices; Determinants, Cramer`s rule; Vectors in 2-space and 3-space, dot product, norm of a vector, projections, cross product, lines and planes; Real vector spaces, subspaces, linear independence, basis and dimension, row space, column space and null space of a matrix, rank of a matrix.
• Discrete Mathematics

  Discrete Math: This is an introductory course in discrete mathematics oriented toward Computer Science. Topics taught in the course include: - fundamental mathematical concepts (definitions, proofs, sets, relations, functions, order relations, proofs by induction), - counting (permutations, combinations, the inclusion-exclusion principle), - basic number theory and graph theory.
• Introduction to Computer Science

  The course equips the students with a solid basis of computer programming, and exposes them to major themes in computer science such as digital architectures, algorithms, complexity and more. The course uses Java as a first programming language, and emphasizes object-oriented software development
• Linear Algebra II

  Course Syllabus - Linear transformations: kernel, image, composition of transformations, the inverse matrix, the duality of matrices and transformations. - Eigenvalues and eigenvectors, the characteristic polynomial, diagonalization of matrices. - Inner products, orthogonality, orthonormality orthogonal matrices
• Data Structures

  As the saying goes, “good data structures and bad code are much better than the other way around”. Indeed, in order to solve challenging problems in an efficient and elegant manner, one must organize one’s data in a suitable form, called data structure. Data structures are an essential area of study and practice for computer scientists and serious software developers. The course presents and analyzes classical data structures and related algorithms. In particular, we will learn how to assess the performance of various algorithms for searching, sorting, and manipulating data. We will learn widely-used data structures such as lists, stacks, queues, trees, and hash tables. In addition, we will then learn the relations between the data structures used and the efficiency of the algorithms using them. Following is a list of subjects to be covered. Time & space complexity: Best case, worst case, average case and amortize. We will use O, Ω,  bounds. List of Data structures: linked list, Stack, queue, Binary Heap, Binary search tree, binary search tree with augmented data (e.g., interval tree), Black & Red trees, B-trees, Hash table, KD- tree, upside-down forest (Disjoint Union / Find). Algorithms: in addition to the algorithms related to the data structures, we will also learn comparison based sorting algorithms (heap sort, quick sort, merge sort), linear sorting algorithms (radix sort, counting sort and bucket sort), Ordered Statistics algorithms, and in particular the median-of-median algorithm. Textbook Introduction to Algorithms by Cormen, Leiserson, Rivest and Stein. (CLRS) A Hebrew translation exists (by Open univ.)
• Logic and Set Theory

  Set theory: naive and axiomatic set theory, cardinals and set comparison, finite and infinite sets, countable sets, cardinality of the continuum, degrees of infinity. Logic: We will study in the course about two logics - propositional logic and first order logic. We will understand the general components of a logic - syntax, semantics, and a proof system - and we will elaborate on each of the components with respect to the two above logics. Among other things, we will study about: Propositional logic - logic connectives, truth tables, logical consequence and equivalence, tautologies and contradictions, normal forms. First-order logic - quantifiers, predicates, functions, structures and models, logical consequence and equivalence, normal forms. As a part of first order logic, we will see examples of algebraic structures, and in particular, we will study basic concepts in group theory.
• Calculus I

  This is the first course in the calculus of one variable intended for Computer Science. Topics covered include the algebraic and analytic properties of the real number system, functions, limits, derivatives and an introduction to integration. Applications including graphing functions, maximising and minimising functions, areas and volumes.
• Calculus II

  The second course in the calculus of one variable intended for Computer Science. Topics include integration, infinite sequences and series, power series and Taylor's series, and an overview of multidimensional calculus.
• System Programming in C

  The main objective of the course is to learn how a computer program operates behind the scenes. Major topics that we will address: - How is data stored for different types (integer and non-integer)? - What are the different memory components of a program (stack vs. heap)? - What are pointers and how are they used? - How can arrays and structures be used to implement objects and data structures? We will learn these topics through programming in C in a Linux environment. Programming in C exposes the programmer to the memory structure of the program. We will learn how to correctly manage memory - via automatic allocation or dynamic allocation. We will also learn how to construct a program using a collection of functions and how to divide it among different files. In parallel, we will cover fundamental topics through working in a Linux environment, such as managing permissions, parsing and modifying text files, and programming in shell scripts. The course will involve programming assignments in C in a Linux environment.

Entrepreneurship Courses

• Entrepreneurship Vertical Elective A

  (Choose 1 out of 9 below)

  1. Cyber and Software Solutions Entrepreneurship - Lecturer: Mr. Ophir Bear.

   

  The course will dive into various pillars of entrepreneurship in both fields of Cyber and Software Solutions . These include relevant business models, ecosystem structure, financial and regulatory issues, risks facing ventures in the field, and existing and developing technologies.

   

   

  2. Consumer Products Entrepreneurship - Lecturer: Gil Lemel

   

  In recent years more and more consumer products have become increasingly ‘smart,’ but nonetheless these are items we can physically hold in our hands. Such products include smart water bottles, digital cameras that can think, and head bands with sensors that monitor the change in the IQ of students during their studies. During this course students gain an understanding of the rules of the game in the consumer products field, examine why and how certain consumer products changed the world (strategy and tactics), and attempt to develop ideas for new products.
  
  

   

   

  3. CannabisTech - Lecturer: Mr. Omer Zerahia

   

  In the course, The Cannabis Market - Entrepreneurship and Business Development, which is the first cannabis course of its kind at Reichman University, we will follow the story of this growing market from its origins to its current status, locally and globally. We will review the incarnations of the Cannabis plant in various territories over the years, diving into the business value chain created around it, from the plant's cultivation stage, through its pharmaceutical products to its supply as a prescribe drug for patients . The final thesis of the course will include initiating, planning, and presenting a business project related to the Cannabis market.

   

   

  4. Biotech Entrepreneurship - Lecturer: Gilad Gome

   

  The course will include basic material in biology, and research of companies utilizing the power of biotechnology to build products and services in medicine, FoodTech, agriculture and more. During the 9th class, students will present their group ideas, of which one will be chosen to be further developed. We will learn about the connection between biology and biotechnology, and how digital health will disrupt the systems of today. 

   

   

  5. Internet & New Media Entrepreneurship - Lecturer: Eran Wagner 

   

  The entrepreneurial process is complex and includes many elements, from idea to the different ingredients of execution. In this course we will try to examine high-tech entrepreneurship in the digital realm and understand its unique characteristics while focusing on basic concepts and their implementation in real businesses in Israel and globally.

   

   

  6. SportTech - Lecturer: Dan Daniel.

   

  This course explores the rapidly growing Sports-Tech and Wellness industry, with a focus on both global trends and Israel’s dynamic ecosystem. Students examine the market, key players, and entrepreneurial opportunities while working on a practical industry project that includes developing a business model, MVP, and investor pitch for a start-up or corporate initiative

   

   

  7. Fashion Tech - Lecturer: Ms. Inbar Carmel.

   

  The global fashion industry, valued at over $2 trillion, is undergoing a major digital transformation known as FashionTech. This course explores how artificial intelligence, data-driven personalization, and innovative marketing reshape everystage of the fashion ecosystem, from production and distribution to consumer experience. Students gain insight into the technologies and trends driving this rapidly evolving industry

   

   

  8. Fintech, Blockchain and Data Science Entrepreneurship - Lecturer: Mr. Yaron Golgher

   

  In this course, we would describe and analyze the disruption of the financial sector and its implications on society. We'll then 'hands-on' explore opportunities for entrepreneurship in this fast-moving sector.

   

   

  9. Real Estate Entrepreneurship - Lecturer: Mr. Ziv Shor

   

  The course will expose students to the real estate investment world and taught from the perspective of the entrepreneur aimed for value creation.
• UX/UI and Product Design for Entrepreneurs

  Lecturer: Dr. Yaacov Greenshpan

  The user experience (UX) and the user interface (UI) are an important element in product design. And successful interface design is almost always a direct result of a match: matching the users' capabilities - as well as their limitations, matching their preferences, attitudes, emotions, needs, and more. In fact, building good interface involves deep understanding of needs, proper analysis of information, extensive knowledge of human capabilities, proper planning and testing and verification with users. This course deals with precisely these key points. The course will focus on learning number of basic tools in the UX world, which relate to the three key stages of building successful UI: analysis, design and testing- not necessarily in this order. The aim of the course is to provide students with theoretical (little) and practical (a lot) information that will give them an introduction to the methods, tools and considerations required for successful product UI design. In addition, the course will provide knowledge and experience in basic design methodologies so that upon completion of the course students will be able to design the user interface and user experience of the products they are building, in a better and more professional way.
• Legal and Tax Aspects of Entrepreneurial Ventures

  Lecturer: Daniel Pomerantz

  In this course, you’ll learn to understand the language of investors and the ideas of finance, how to build the right legal structure for smooth relations with your business partners, and how to run a professional company. We will follow the entire journey of a company from startup to exit or maturity.
• Financial Management & Entrepreneurial Finance

  Lecturer: Dr. Tal Mofkadi

  This is a first course in finance that is designed to introduce students to the concepts and techniques necessary to analyze and implement optimal investment decisions by firms and managers. Special emphasis will be put on understanding and analyzing the financial section of a business plan.The course studies the effect of time and uncertainty on decision making. Topics include basic discounting techniques, projects' investment decision making, stock and bond valuation, capital budgeting under certainty and uncertainty, and asset pricing models.
• Entrepreneurship Vertical Elective B

  (Choose 1 out of 8 below)

  1. Clean-tech & Sustainability Entrepreneurship - Lecturer: Ms. Anat Tsour Segal.

   

  We will explore the diverse technology landscape and the innovative business models that are transforming environmental crises across the globe into startup opportunities. Participants will also gain hands-on experience with key executive tools for assessing “circularity” and sustainability impact of early-stage ventures.

   

   

  2. VC Fund - Lecturer: Mr.Amit Pilowsky

   

  This course deals with the establishment and management of venture capital funds and other tools for venture capital investments. Related topics include: The relevant players, different types of investors, Fund investment strategies, similarities and differences between various types of funds, cultivating the portfolio of the ventures after the investment and Entrepreneur - Investor relationships.

   

   

  3. Impact Entrepreneurship - Lecturer: Dr.  Iris Lubitch

   

  Global surveys report an increasing commitment by entrepreneurs and investors to building impact ventures – i.e., businesses established to generate competitive financial returns alongside significant measurable social and environmental Impacts. The objective of this course is to provide a framework for understanding the different models that are emerging for guiding the establishment of impact ventures. The course also provides an overview of methodologies that have been developed to measure and report social and environmental impacts, as well as guiding principles for evaluating the viability of potential impact ventures.

   

   

  4.Gaming Entrepreneurship - Lecturer: Yariv Lissauer.

  Sponsored by Playtika

   

  The course will cover the following subjects: introduction to gaming, structure of the ecosystem in the world of gaming and its main players (organizations and people) in Israel and the world. Types of entrepreneurship in the field of gaming, business models accepted and developed in the world of gaming, regulatory aspects, financial issues and fundraising, relevant technologies in gaming (existing and developing), and more.

   

   

  5. Cross Vertical Acceleration - Lecturer Prof. Dafna Kariv. 

   

  This applied course is designed for students who have begun developing a venture and wish to advance it toward programs such as acceleration, venture establishment, or Zell in their third year. Students work individually or in teams to refine their ideas, test market and product feasibility, build strategic partnerships, connect with mentors and investors, and develop a sustainable business plan. The course includes pitching to evaluators and engaging with key figures in the entrepreneurial ecosystem. It offers a unique opportunity to strengthen an early-stage venture during the second year and prepare it for further development

   

   

  6. The Psychology of Language in Innovation & Entrepreneurship - Lecturer: Dr. Orly Idan.

   

  This course examines the power of language as a driver of creativity, communication, and innovation. Students explore persuasive storytelling, brand building, and cross-cultural communication to strengthen entrepreneurial impact. By understanding how language shapes consumer behavior and market research, participants gain tools to make strategic decisions and lead effectively in dynamic, diverse business environments.

   

   

  7. Organization Innovation with Digitization, AI & Robotics - Lecturer: Mr. Tom Hitron

   

   

  8. Power and Influence in Entrepreneurship - Lecturer: Ms. Yasmin Lukatz
• Product Management for Entrepreneurs

  Ms. Tamar Schultz

  Product Management is key to the success of any company, and hi-tech companies in particular. The purpose of this class is to teach students the principles of product management and share practical lessons learned over the years. How to identify and articulate a problem, and define the right solution. We will cover a variety of research and validation techniques. The Product Manager Role (Responsibilities and Tasks, B2B vs. B2C) , The PM Ecosystem (Interaction with stakeholders, Working in a large company vs. a startup) , Product Definition , Product Execution and Business Go to Market (Business model and pricing, Messaging and Positioning and Working with Customers and Sales).
• Digital Marketing for Entrepreneurs

  Lecturer : Ofir Richman

  The rapid changes and development of technologies, devices, platforms and channels have transformed our world. Media consumers are changing and with them the tool set used by marketers and advertisers. Media fragmentation, social networks, multi-screen devices, and technology empowered consumers have created new challenges for marketers.  Consumer’s attention is not seized by interruption, but earned by engaging them in a brand’s essence, its blueprint. The course will examine the changes traditional marketing has been going through to adapt to a digital landscape and the impact on marketing advertising and branding strategies. Emphasis will be put on building a brand “story”. Students will be teamed up with existing startups and learn to build a cross platform strategic campaign to meet their growth and marketing challenges. They will understand how to incorporate marketing tools into the process.  Students will gain additional hands on experience by building a Google AdWords' campaign.
• Machine Learning

  Lecturer: Prof. Ilan Gronau

  An introductory level machine learning course. We will present the main principles of data-driven learning algorithms. We will provide the theoretical basis for learning algorithms and learn about the pros and cons of different approaches, from both a mathematical and a practical point of view.
• Accounting Skills for Entrepreneurs

  Lecturar: Mr. Eran Yohan

   In course will provide the students with an accounting perspective of the business world, while providing basic tools to read and understand financial statements and to be familiar with companies' KPIs and business models.

Computer Science Courses

• Algorithms

  The course covers fundamental ideas in the design and analysis of Algorithms. A thorough knowledge of algorithms allows a computer scientist to determine what problems can be solved using a given amount of resources. The tools and techniques used for the basic algorithms covered in this course can be adapted to provide efficient solutions to novel problems.
• Introduction to Probability

  Probability theory is a tool of fundamental importance to nearly all the sciences, including Computer Science. This course is intended as an elementary introduction to the mathematical theory of probability. The course covers the following topics: Basic Terms in Probability: Probability Spaces (Sample Space, the Field of Events and the Probability Function), Axioms of Probability, Combinatorial Analysis and Symmetric Sample Space, Conditional Probability and Baye’s Rule, Independency between Events. Random Variables: General Discrete Distributions and Special (Uniform, Geometric, Binomial, HyperGeometric, Poisson, Negative Binomial) and General Continuous Distributions and Special (Uniform, Exponential, Erlang, Normal), Jointly Distributed Discrete Random Variables, Independent Random Variables, Discrete Conditional Distributions, Expectation, Variance, Correlation (CoVariance, Correlation Coefficient), Markov and Chebyshev inequalities, Limit Laws (Central Limit Theorem, Convergence in Probability, the Weak Law of Large Numbers).
• Operating Systems

  This course introduces the logical design of operating systems, emphasizing multi-programmed operating systems and multi-user information systems. The main topics that are discussed in the course are: processes, synchronization, memory management, file systems, I/O devices.
• Computational Models
• Advanced Programming

  In this course we will cover essential tools that enhance any programmer's toolbox. We will discuss advanced Java topics (that were not covered in the intro class), distributed version control, Python, SQL, HTML, JavaScript and CSS. We will emphasize self-learning, and will touch upon general programming topics such as debugging and unit-tests. The course will give students a solid footing in each topic, that will allow them to keep exploring on their own.

   
• Machine Learning from Data

  An introductory level machine learning course. We will present the main principles of data-driven learning algorithms. We will provide the theoretical basis for learning algorithms and learn about pros and cons of different approaches, from both a mathematical and a practical point of view.

  Students will implement and use algorithms and will practice their application in real life data contexts. Homework and examples will be based on python code developed by the students as well as, in special cases, on using python/sklearn packages.

  Subjects covered include:

  1. 1. Linear models: regression, logistic regression, feature selection
  2. 2. Decision trees , including different approaches to splitting nodes and

  pruning techniques

  3. 3. Bayesean learning, including the advantages and disadvantages of naive vs full Bayes approaches
  4. 4. The perceptron - both primal and dual
  5. 5. kNN
  6. 6. Density estimation and EM
  7. 7. SVMs, including hinge/slack variables and how they affect results
  8. 8. Unsupervised learning - clustering techniques
  9. 9. PAC learning and sample complexity
  10. 10. VC dimension
  11. Statistical estimates of error rates

Mandatory Courses The students must choose one of two mandatory courses

• Digital Architectures

   

  This course reveals the inside of digital computers. The purpose of the course is to explain the principle of operation of the hardware and the relation of the hardware and the software and to give a clear view of how a high-level language program is actually executed by a digital computer. The course starts with Boolean algebra and the implementation of Boolean equations using gates and continues with forming the basic bui lding blocks of a digital computer, e.g., multiplexers, decoders, Arithmetic Logic Unit, registers, counters, state machines etc. At this stage, a simple CPU can be designed. Therefore, a RISC CPU, the MIPS, is defined by introducing its instruction set. The steps of converting a high level program into the MIPS machine language and the mechanism needed to support subroutines are discussed. This is followed by implementation of a basic single cycle MIPS in which the data path and the control part are designed in detail. The next stage is a multi-cycle implementation of the same CPU, including exceptions and interrupts handling. Eventually, a pipelined version is introduced. We will also show the similarity between the MIPS instruction set and RISC-V instruction set. The RISC-V is nowadays the open source for computer architecture.
• Digital systems

  This course, also known as Nand to Tetris, walks students in the construction of a modern general-purpose computer - hardware and software - from first principles. We will start from the most basic logic gate, known as Nand, and develop from it more gates and chips, leading up to a CPU, memory, and a computer architecture. This will be done using a Hardware Description Language and simulators, like computers are actually developed in industry. We will then develop an assembler, a virtual machine, a compiler for a simple, Java-like programming language, and a basic operating system. We will end this journey by developing a simple computer game like Tetris. It will be a thrill to see this game running on a computer that you built from the ground up. The course provides a deep understanding of many topics in applied computer science, as well as significant system development experience.

Entrepreneurship Courses

• Final Capstone Project A+B

  Triple A, Venture Creation Track, Value Creation and Business Development Track, Venture Capital Track, Innovative Research Track, Case Study Track or Special Programs (Zell, Exchange Students, Game Changers, Zvi Meitar etc...)
• Advanced Entrepreneurial Electives A

  Choose 1 out of 3 below

  1. Advanced Digital Marketing for Entrepreneurs - Lecturer: Mr. Yair Koren

   

  How to manage the advanced digital marketing of a real business, using platforms such as YouTube, Facebook, and Instagram, in addition to Google. Students will promote their own startup (i.e., their final project) or any other company they choose, build a website in WordPress, and promote the site on Google (SEO). In addition, we will promote the business on social media (organic and sponsored), work with pixels, and learn to use advanced analytical tools to improve the performance of our site and campaigns.

   

   

  2. Venture Branding and Storytelling - Lecturer: Oded Lavie 

   

  A journey of storytelling and branding for entrepreneurs. During the course we will review the history of branding and storytelling, talk about the research which has been conducted in this space, but most importantly learn about the tools and techniques that can help create meaningful and inspiring stories.

   

   

  3. Venture Creation Game-Based Learning - Lecturer: Omer Zerahia.

   

  This fully online course explores the craft of entrepreneurship, strategy formulation, and implementation that drive competitive organizations. In this course, teams of students will initiate and operate a virtual start-up, competing among themselves. Acting as the company's executive team, students will steer the company's direction through interdisciplinary decision-making in an uncertain environment, grappling with business fundamentals and the interplay between marketing, distribution, manufacturing, human resources, finance, and accounting across multiple decision cycles.
• Advanced Entrepreneurial Electives B

  Choose 1 out of 3 below

  1. Business Analysis for Entrepreneurs using Data Science - Lecturer: Mr. Ori Kaz.

   

  This course covers different aspects of the data science work with emphasis on machine learning for entrepreneurs. The students will learn to clean and prepare datasets, define the data science experiment, and apply and evaluate different machine learning algorithms in order to solve business-oriented problems. The course provides useful knowledge for students interested in getting into the data science world as well as for those looking to understand the methodologies and challenges in it.

   

   

  2. Value Creation and Project Management - Lecturer: Alex Coman

   

  Students learn how to map the Arena for their business venture. The Arena is used to design the product strategy, to assess the value potential of opportunities, how to crystalize essential/killer features and how to deliver the concept in an agile manner. Students gain a coherent toolkit for the diagnosis of organizational strengths and weaknesses, and the creative generation of options in the supply chain ARENA

   

   

  3. From Sales to Customer Success - Lecturer: Mr. Erez Ezra.

   

  The Course focuses on one of the most important aspects of organizations, Sales and Customer's Journey. How do organizations get leads from the Marketing team, make them paying customers and eventually satisfied and loyal partners.

   

   

  4. Sales and Business Development in Startups and High-Tech Companies - Lecturer: Mr. Hadar Tal.

   

  This course introduces key principles of sales and business development in startups and high-tech companies. Students learn how to define target markets, choose business models, build sales infrastructures, generate and convert leads, and acquire first customers. The course also covers sales team management, negotiation and deal closing, direct and indirect sales strategies, regional sales approaches, and the creation of annual sales plans
• Organizational Behavior for Ventures and Innovative Projects

  Prof. Tamar Almor

  The course focuses on human resource management within the context of ventures and innovation projects, emphasizing the adaptations required at various stages and sizes of the organization, from small startups to medium-sized and large organizations, and up to large-scale enterprises.
  We will examine the unique challenges and strategies necessary for managing and cultivating innovation-supportive work environments. Additionally, we will explore how organizations can address the uncertainties associated with innovation.

Computer Science Courses

• Complexity Theory

  This is a mathematical class in which we will study the capabilities and limitations of efficient computation. We will classify various computational problems into different classes according to the amount of resources they require and prove reductions between them. We will then introduce more advanced algorithmic techniques (such as randomized algorithms and approximation algorithms) and study their limitations as well.

  Topics include: time complexity, the classes P and NP, polynomial time reducibility between problems, the Cook-Levin theorem and the theory of NP completeness, self-reducibility and reducibility between search, optimization and decision problems, space complexity, randomized algorithms, approximation algorithms.
• Computer Networks

  This course is organized around the five-layer Internet architecture. These five layers consist of the application, transport, network, link, and physical layers . The course covers fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: overview of network architectures, applications, network programming interfaces (e.g., sockets), transport, congestion, routing, and data link protocols, addressing, and distributed algorithms/systems. Examples of protocols will be drawn primarily from the Internet (e.g.,HTTP, SMTP, DNS, TCP, UDP, IP, RIP, OSPF, DHCP, ICMP, Ethernet, etc). In addition, we will also cover several Distributed Algorithms. There will be five assignments and a final exam. This course is intended for third year undergraduate computer science.

   
• CS Elective Courses

  In the third year you need to choose one computer Science Elective Courses