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.

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.

The main objective of the Art of Public Speaking is to provide students with effective communication tools that improve their presentations in front of audiences of any kind. Participants learn how to define short and coherent verbal messages, while convincingly using their non-verbal bridges – body language, voice and eye contact. Throughout the lecture they receive practical ideas regarding how to successfully implement these tools in their self-presentations, lectures and also while communicating in virtual spheres. Students will master these tools in a manner that will enable them to succeed even when the time they have to convey their messages is extremely short and the audience is skeptical.

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!)

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 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.

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

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

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.)

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.

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.

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.

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.

***Impact Entrepreneurship - Lecturer Dr. Adiv 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.

***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.

*** 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.

***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.

***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.

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. Course program and reading list Semester 1 Year 2024 School: Adelson School of Entrepreneurship B.A BioTech Entrepreneurship Lecturer: Mr. Gilad Gome gilad.gome@post.runi.ac.il Course No.: 3071 Course Type : Workshop Weekly Hours : 3 Credit: 3 Course Requirements : Final Paper Group Code : 242307100 Language: English Prerequisites Students who took one of the courses listed below will not be allowed to register to the course BioTech Entrepreneurship (3071): 26019 - Biotech Entrepreneurship We will learn about DNA as a software, cells as computers, and the human body and nature as fields which inspire innovation. We will learn about current and future needs of humanity that are currently unmet, and how biotechnology will tackle these problems and needs.

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.

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.

• Fintech, Block chain 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.
• 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.
• 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.

• 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.

• VC Funding- 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.

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).

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.

The main objective of this course is to get you familiar with machine learning fundamentals and terminology, and to comprehend how Data Science can be utilized for business value creation. This will include examples of basic hands on demonstrations of Data Science methods in Python.

Many business problems in the financial, marketing, advertisement, management, healthcare, etc. require data analytics tools to analyze the massive amount of data collected by the organization, and transforming the raw data into meaningful business insights. In the course we will discuss methods to analyze data and make recommendations such as Naïve Bayes, as well as clustering technologies like K-mean, and will learn how to use them to translate the data into recommendations for solving business problems.

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.

 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.

The course covers techniques for design and analysis of algorithms, and introduces important and widely used algorithms. The course is theoretical in nature, concentrating on the abstract notions involved. Basic graph algorithms such as graph traversals, shortest path, minimum spanning tree, and network flow are covered as well as general techniques such as greedy algorithms and dynamic programming.

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.

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 building 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.

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).

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.

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.

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

Accelerator Track, Venture Creation Track, Innovation and Intrapreneurship within Organizations Track, Venture Capital Track, Personal Research Track or Special Programs (ZELL, Exchange Students, Zvi Meitar, etc...)

• Advanced Digital Marketing for Entrepreneurs - Mr. Yair Koren - Description: 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.
• Venture Branding and Storytelling - Oded Lavie - Description: 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.
• - AI Applications for Entrepreneurs -  Mr. Dudi Kalmanson

  In this course, students will learn AI technologies and tools that will be used by them in the establishment and management of ventures. The students will discover that with the help of understanding these innovative tools, they can have a power multiplier in the various related fields for ventures. Students will learn what can be accomplished with these tools now and in the future. They will be exposed to the newest technologies on the market, the limitations, and dangers of using these tools, and how to overcome them.The course will focus on three main areas: the creation of the product (Proof Of Concept), marketing and, analysis of data.

• Business Analysis for Entrepreneurs using Data Science -  Mr. Ori Kaz. Description: 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.
• Value Creation and Project Management - Alex Coman Description: 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
• 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.

The course reviews challenges of maintaining a moral compass while trying to make your venture a unicorn. The course will try to define ethics frameworks through interactive discussions and guest lectures. The goals of this course are to familiarize students with real life dilemmas, the inability of the law to set clear borders and players which are affected by decisions made in the entrepreneurial ecosystem. Course topics include ethics in artificial intelligence (AI), privacy and user data aspects, competition effect on ethics, and ethics of venture capital and fundraising.

The course will combine a mix of didactic teaching of theory and research with experiential exercises and technique development, in order to understand the relationship between failure and success and to develop tools to manage inevitable hurdles. Using theoretical and practical ideas from the psychology of wellbeing, the course will culminate in developing the essential life principles of resilience and grit.

In this course we will discuss behavioral economics concepts and the psychological approach to decision making., and how can we use these concepts to our advantage and create better outcomes for our business? Now more than ever, it’s critical for product organizations to know the science underneath human behavior and how to apply it. In a competitive and crowded space, Behavioral Design is crucial for both user and company success. We will learn different biases and discuss how to use behavioral science in ways that maximize the benefit for both the user and the business.

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, Advanced Programming, or Machine Learning from Data

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.