Introduction To Python Programming And Developi... _TOP_

The Summer School will begin with an introduction into programming and the mathematical foundations essential for the success of data scientists. This is part of the technical preparation for the Master of Data Science for Public Policy programme at the Hertie School and is also open for the general public.

Introduction to Python Programming and Developi...

The course starts with some fairly simple introductions to HTML and CSS and what each programming language is used for when it comes to web design. Later on, it delves into more advanced techniques and concepts, such as UI design and optimization.

Finally, a web page was developed to access the text extracted from the pictures taken by the camera over a network. Web programming was done using the Hyper-text Markup Language (HTML) on the python IDE. An IP address 0.0.0.0/5000 was used on the network of the web page. The web page can be accessed by anyone on the same network as the Raspberry Pi. The diagram below shows a sample of the text from the designed web page.

In this work, a highly efficient, economical, and VRPN system was developed. This system uses smart IR sensor to detect moving objects, camera to capture the image, extract the text from the image, and save the text on a web page. The major component selected to do the main work in the system is the Raspberry Pi. OpenCV was used together with python programming, for the character segmentation and recognition. This was configured on the Raspberry Pi, including the required library that is required to make the hardware components of the system to work with the Raspberry Pi. As shown in the results, the developed system was able to deliver a clear and readable text on a web page which can be used to query a database. Due to the calibration of the IR sensor, it is able to detect fast-moving cars and also able to log different cars at different times using a tag for each data it receives and having a unique saving sequence. The system is by far one of the cheapest means for the actualization of traffic management in a smart city.

3 Credits Operations Management MG-GY6303 This course focuses on developing a deeper understanding of the role that operations management plays in determining business strategy and in developing competitive advantage. The primary emphasis is on how to develop and effectively manage operations in knowledge-intensive enterprises. Participants discuss the operational design and managerial implications when the emphasis of the operations group is more on knowledge management than on production and facilities management; managing the effective integration of technology, people and operating systems; understanding the complexities and challenges of operations management; the challenges of developing and managing supply chain networks; and the critical role of technology in developing operational capabilities in an organization. Prerequisite: Graduate Standing 3 Credits Marketing MG-GY6073 This course emphasizes the imperative to be customer-focused in the information sectors. Topics include market definition and redefinition due to technological change; analysis of customer decisions; strategic choices of markets and products; positioning for competitive success; product pricing, distribution and communications decisions; new product development; market-system dynamics and the value chain. Prerequisite: Graduate Standing 3 Credits Human Resource Management MG-GY6123 Introduction to the broad range of human resource functions and their organizational role. Addresses issues in managing people that impact not only HR professionals but also line managers. The course is divided into four modules: (1) an overview of HRM from a strategic perspective; (2) the management of human resources, including recruitment and selection, performance management, compensation and benefits, training and career support; (3) human resource challenges, including diversity, procedural justice and ethics, collective bargaining and managing change and innovation; and (4) professional roles in HRM. Prerequisite: Graduate Standing 3 Credits Management of Information Technology and Information Systems MG-GY6503 This course is designed for managers who need to understand the role and potential contribution of information technologies in organizations. The focus of the course is on different information technologies and their applications in managing business critical data, information and knowledge. The course concentrates on the current state of IT in organizations, challenges and strategic use of IT, IT infrastructure and architecture, building, implementing and managing IT applications, and emerging issues such as intelligent systems, business process reengineering, knowledge management and group support systems. Prerequisite(s): Graduate Standing 3 Credits Statistics for Data Analysts MG-GY6193 The course is an excellent introduction to statistical tools used in any aspect of business. It covers thoroughly key probability concepts and statistical techniques used in the analysis of financial, economic and accounting data. In addition to descriptive statistics, probability, and hypothesis testing, this course also covers regression analysis and time series analysis with an emphasis on model formulation and interpretation of results. The use of spreadsheets (to facilitate most of the analysis in this class) will be introduced and developed as well through case studies based on real-world data and problems in business and economics, so you will have acquired a working knowledge of spreadsheet after this class. The focus is on understanding underlying concepts rather than on memorizing mathematical formulas while the lectures concentrate on statistical concepts and applications using spreadsheets rather than rigorous math proof for the entire semester. Prerequisites: Graduate Standing 3 Credits Communication for Technology Managers MG-GY6183 This highly interactive and participative experience introduces powerful concepts and approaches for effective technical communication, strategy, and delivery. Deliverables will include written documents and oral presentations. You will present both individually and in a team, and will receive feedback to improve your presentation effectiveness. Prerequisites: Graduate Standing 3 Credits Data Visualization for Business Intelligence MG-GY6203 Huge volumes of data are generated, stored and analyzed to drive complex technical and business decisions by providing actionable insights. To achieve this end-users across the industry, need to visualize the data in diverse representations and perform explanatory and exploratory analysis. The course will provide a graduate-level introduction to Data Visualization, as a human perception friendly approach to convey concepts and analysis based on appropriately presented field data. It will systematically introduce building blocks, including types of data, visual elements and design approaches with many examples; provide a basic introduction to the latest visualization software tools as well as programming technologies, such as R and D3; and review several case studies of their application in producing business intelligence. 3 Credits Supply Chain Management MG-GY6463 This course introduces supply-chain management and covers its qualitative and quantitative aspects. The underlying objective is to: (1) introduce students to the standard business concepts (and associated terminology) involved in the retailing and supply-chain management; (2) develop skills in understanding and analyzing retailing, marketing, logistics, operations, channel management and allied issues and the interactions between them; and (3) examine and discuss the important role played by technology and integration at various points in the supply chain. Prerequisite: graduate standing. 1.5 Credits Internship for MS I CP-GY9911 Internship is a supervised, creative experience that provides full-time graduate students with the opportunity to enhance and augment classroom learning experiences in their field of study. The experience culminates in written reports, from the student, to the faculty supervisors as well as written reports from the supervisor. Prerequisites: Advisor's approval. 1.5 Credits Internship for MS II CP-GY9921 Internship is a supervised, creative experience that provides full-time graduate students with the opportunity to enhance and augment classroom learning experiences in their field of study. The experience culminates in written reports, from the student, to the faculty supervisors as well as written reports from the supervisor. Prerequisites: Advisor's approval and CP-GY 9911

1.5 Credits Programming for Business Intelligence and Analytics MG-GY8401 Data will increasingly drive business decisions across industries. While statistics provides methods for analyzing, forecasting and evaluating data, programming provides methods for extracting, manipulating and visualizing data. This 1.5 credit course will meet for 7 weeks throughout the semester to complement Statistics for Business Analysts. Through a focus on case studies, students will gain the programming experience needed for electives in several knowledge areas pertinent to data science. By learning integrative approaches to formulating problems, students can take programming out of the lab and into industry. 1.5 Credits Data Engineering MG-GY8411 This course complements Statistics for Business Analysts, in coordination with Programming for Business Intelligence and Analytics. Through a focus on case studies, students will gain the experience needed for electives in several knowledge areas pertinent to data science. By learning how to structure and organize data for descriptive (unsupervised) and predictive (supervised) modeling, students can take preparation of data for AI out of the lab and into industry. 3 Credits Business Analytics MG-GY8413 Business analytics is a set of data analysis and modeling techniques for understanding business situations and improving business decisions. This course introduces business analytics concepts, methods and tools with concrete examples from industry applications. In the first part of the course, we will focus on descriptive analytics and exploratory data analysis concepts with a refresher on basic probability and statistics. In the second part, we will cover principles, techniques, and techniques for spatial data, time series, and text as data. The final part of the course will introduce a project that links business impact and modern data analytics techniques for managerial decision making in functional areas, including finance, marketing, and operations. Prerequisites: (MG-GY 6193 or MG-GY 9753) and MG-GY 8401 and Graduate Standing 3 Credits Management Science MG-GY6103 This course introduces major concepts and methods associated with Management Science, which deals with the application of quantitative modeling and analysis to management problems. Students learn to employ important analytical tools, to determine the assumptions used, and to recognize the limitations of such methods. The course discusses methods of linear and nonlinear programming, queuing, decision analysis, simulations and game theory. The course also introduces modeling with spreadsheets. Prerequisite: Graduate Standing 3 Credits Machine Learning for Business MG-GY8423 Machine learning is about extracting or discovering knowledge from data. This course will cover fundamental machine learning algorithms used to understand business situations and improve business decisions. In machine learning, there are three types of commonly used algorithms: supervised (predictive), unsupervised (descriptive) and reinforcement learning algorithms. In the first part of the course, we will focus on supervised learning algorithms including K-Nearest Neighbors, Linear Regression, Logistic Regression, Decision Tree, Support Vector Machine (SVM), Naive Bayes, bagging and boosting algorithms. The second part of the course will cover unsupervised algorithms including K-means clustering and dimensionality reduction. The last part of this course will cover Reinforcement learning algorithms, especially Markov Decision Process. We will use python as our main programing language. Prerequisites: (MG-GY 8413 or MG-GY 9753) and MG-GY 8401 and Graduate Standing 041b061a72