Courses tagged with "Business" (1739)

Are you tired of hearing that your computer has a virus? Or that your email account has been hacked? Now, is the time for you to protect yourself by understanding the basics of cyber security.

This computer science course presents an introduction to cyber security showing different aspects of this discipline. You will learn what the main existing cyber security threats are and how to protect yourself against them. The course presents a practical approach in which all required material will be provided to allow you to better understand attacks and establish appropriate countermeasures.

Taught by instructors with years of experience in the field of computer security, this course will pave the way to the security area of IT-related professions.

This economics course provides an introduction to the field of cybersecurity through the lens of economic principles. Delivered by four leading research teams, it will provide you with the economic concepts, measurement approaches and data analytics to make better security and IT decisions, as well as understand the forces that shape the security decisions of other actors in the ecosystem of information goods and services.

Systems often fail because the organizations that defend them do not bear the full costs of failure. In order to solve the problems of growing vulnerability to computer hackers and increasing crime, solutions must coherently allocate responsibilities and liabilities so that the parties in a position to fix problems have an incentive to do so. This requires a technical comprehension of security threats combined with an economic perspective to uncover the strategies employed by cyber hackers, attackers and defenders.

The course covers five main areas:

1. Introduction to key concepts in security economics. Here, we provide an overview of how information security is shaped by economic mechanisms, such as misaligned incentives, information asymmetry, and externalities.
2. Measuring cybersecurity. We introduce state of the art security and IT metrics and conceptualize the characteristics of a security metric, its challenges and advantages.
3. Economics of information security investment. We discuss and apply different economic models that help determine the costs and benefits of security investments in network security.
4. Security market failures. We discuss market failures that may lead to cybersecurity investment levels that are insufficient from society’s perspective and other forms of unsafe behaviour in cyber space.
5. Behavioural economics for information security, policy and regulation. We discuss available economic tools to better align the incentives for cybersecurity, including better security metrics, cyber insurance/risk transfer, information sharing, and liability assignment.

After finishing this course, you will be able to apply economic analysis and data analytics to cybersecurity. You will understand the role played by incentives on the adoption and effectiveness of security mechanisms, and on the design of technical, market-based, and regulatory solutions to different security threats.

Our daily lives, economic vitality, and national security all revolve around technology. Our dependence on technology means we need a stable, safe, and resilient cyberspace. However, computers and networks are being misused at a growing rate both by cybercriminals and by our own employees. In this computer science course, you will learn the fundamentals of cybersecurity and basic threats. You will also learn to build a comprehensive security plan that integrates people, processes, and technology, and how to begin protecting yourself and your information.

You will be exposed to areas of personal and physical security, best practices for using our computers and mobile devices, and how we protect our privacy and secure our devices and networks against attacks.

We will examine cybersecurity standards, laws, and ethical issues, the impact of cyber terrorism, how governments use technology and computer systems to defend and attack adversaries, and the effect this has on privacy and individual liberties. We will also explore why IT administrators and cybersecurity professionals need to demonstrate adherence to ethical principles.

Finally, we will look at the important areas of data breach planning and business continuity, both of which are critical to the long-term viability of an organization.

This course will also focus on the types of careers within the cyber security field and how you can enhance your career through professional certifications.

No prior knowledge or skills are required except for basic computer literacy.

EECS149.1x introduces students to the design and analysis of cyber-physical systems --- computational systems that are integrated with physical processes. Applications of such systems include medical devices and systems, consumer electronics, toys and games, assisted living, traffic control and safety, automotive systems, process control, energy management and conservation, environmental control, aircraft control systems, communications systems, instrumentation, critical infrastructure control (electric power, water resources, and communications systems for example), robotics and distributed robotics (telepresence, telemedicine), defense systems, manufacturing, and smart structures.

A major theme of the course is on the interplay of practical design with formal models of systems, including both software components and physical dynamics. A major emphasis will be on building high confidence systems with real-time and concurrent behaviors. Students will apply concepts learned in lectures to programming a robotic controller in a specially-designed virtual laboratory environment with built-in automatic grading and feedback mechanisms.

This edX course is an online adaptation of the UC Berkeley undergraduate course EECS 149, covering a subset of topics that are especially relevant for the lab component of that class.

This capstone includes the evaluation of the competencies and performance tasks, which define a successful cybersecurity defense.  

This capstone is part of the RITx Cybersecurity MicroMasters Program that is specifically designed to teach cybersecurity techniques and tools needed to effectively defend systems and networks of a corporate environment or enterprise.

In order to qualify for the MicroMasters Credential you will need to successfully earn a Verified Certificate in each of the four RITx Cybersecurity courses as well as pass this final capstone.

The capstone will test knowledge and skills across all 4 courses in the Cybersecurity MicroMasters Program. It will include hands-on lab exercises that build on the assessments in the previous four courses.

In this introduction to the field of computing security, you will be given an extensive overview of the various branches of computing security. You will learn cybersecurity concepts, issues, and tools that are critical in solving problems in the computing security domain.

You will have opportunities to learn essential techniques in protecting systems and network infrastructures, analyzing and monitoring potential threats and attacks, devising and implementing security solutions for organizations large or small.

This offering is part of the RITx Cybersecurity MicroMasters Program that prepares students to enter and advance in the field of computing security.

Cybersecurity risk management guides a growing number of IT decisions. Cybersecurity risks continue to have critical impacts on overall IT risk modeling, assessment and mitigation.

In this course, you will learn about the general information security risk management framework and its practices and how to identify and model information security risks and apply both qualitative and quantitative risk assessment methods. Understanding this framework will enable you to articulate the business consequences of identified information security risks. These skills are essential for any successful information security professional.

The goal of this course is to teach students the risk management framework with both qualitative and quantitative assessment methods that concentrate on the information security (IS) aspect of IT risks. The relationship between the IT risk and business value will be discussed through several industry case studies.

First, you will learn about the principles of risk management and its three key elements: risk analysis, risk assessment and risk mitigation. You will learn to identify information security related threats, vulnerability, determine the risk level, define controls and safeguards, and conduct cost-benefit analysis or business impact analysis.

Second, we will introduce the qualitative and quantitative frameworks and discuss the differences between these two frameworks. You will learn the details of how to apply these frameworks in assessing information security risk.

Third, we will extend the quantitative framework with data mining and machine learning approaches that are applicable for data-driven risk analytics. You will explore the intersection of information security, big data and artificial intelligence.

Finally, you will analyze a series of extended case studies, which will help you to comprehend and generalize the principles, frameworks and analytical methods in actual examples.

This offering is part of the RITx Cybersecurity MicroMasters Program that prepares students to enter and advance in the field of computing security.

In this course, you will focus on the pathways to cybersecurity career success. You will determine your own incoming skills, talent, and deep interests to apply toward a meaningful and informed exploration of 32 Digital Pathways of Cybersecurity.

You will complete a self-assessment comprised of elements needed to determine essential next steps on your career path.

The Chief Information Security Officer (CISO) in any given organization serves a leadership position, protecting the data and digital systems that a company’s employees as well as its customers depend upon.

This course delves into the role that the CISO plays in cybersecurity operations.

Throughout the lessons, learners will explore answers to the following questions: How does cybersecurity work across industries? What is the professionals' point of view? How do we keep information secure?

Coursework will fully explore the CISO’s view from the top, as well as the position’s toolkit, which includes policy, procedures and practices, technologies, awareness training, and audit. It will also dive into the approaches taken in private industry, government, academia, and the military.

Once heralded as the ultimate vehicle for open communication and self-expression, the internet is rapidly becoming a globally networked surveillance device. Serious threats to national security, combined with the seemingly endless capacity of digital processing and storage, have led to levels of data capture and 24/7 monitoring of individuals’ activity that were unimaginable even a decade ago.
 
With resistance to such practices rising, this course will equip you to take an active part in the debate. You will gain a broad understanding of the competing tensions of the laws related to national security and personal and commercial privacy in the post-Snowden online environment. You will also grasp the looming consequences of this battle for peace, sovereignty, human rights and the internet itself.

Want to study for an MBA but unsure of the basic data analysis still required? This online course prepares you for studying in an MBA program.

Data analysis appears throughout any rigorous MBA program and in today’s business environment understanding the fundamentals of collecting, presenting, describing and making inferences from data sets is essential for success.

The goal of this course is to teach you fundamental data analysis skills so you are prepared for your MBA study and able to focus your efforts on core MBA curriculum, rather than continually playing catch-up with the underlying statistical knowledge needed.

We also hope that learning these data analysis skills will equip you with the ability to understand, to a greater degree, the data you encounter in your working lives and in the world around you - an essential life-skill in today’s data driven environment

This course assumes no prior knowledge of data analysis. Concepts are explained as clearly as possible and regular activities give you the opportunity to practice your skills and improve your confidence.

This course is part of the MITx MicroMasters program in Data, Economics, and Development Policy (DEDP). To audit this course, click “Enroll Now” in the green button at the top of this page.

To enroll in the MicroMasters track or to learn more about this program and how it integrates with MIT’s new blended Master’s degree, go to MITx’s MicroMasters portal.

This statistics and data analysis course will introduce you to the essential notions of probability and statistics. We will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. We will illustrate these concepts with applications drawn from real world examples and frontier research. Finally, we will provide instruction for how to use the statistical package R and opportunities for students to perform self-directed empirical analyses.

This course is designed for anyone who wants to learn how to work with data and communicate data-driven findings effectively, but it is challenging. Students who are uncomfortable with basic calculus and algebra might struggle with the pace of the class.

Are you ready to leave the sandbox and go for the real deal? Have you followed EX101x Data Analysis: Take It to the MAX() and EX102x Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis?

In this project-based course you will engage in a real data analysis project that simulates the complexity and challenges of data analysts at work. Testing, data wrangling, Pivot Tables, sparklines? Now that you have mastered them you are ready to apply them all and carry out an independent data analysis.

For your project, you firstly get one raw dataset, which you will turn into a dashboard, step by step. You will begin with a business question, and then touch upon different business domains, such as revenue management, planning, scheduling, management, investment, etc.

The progress of the project will be gradual – in the first weeks you will be guided by quizzes to make sure that you are on track. You will engage with creating first drafts of your work and discuss them with your peers.

In the final week, you will be in charge. You will get a second dataset and a number of questions to answer, and it is up to you to design and build the perfect dashboard.

This course will allow you to practice the skills you’ve gained in previous Data Analysis XSeries courses and prove you can be an indispensable asset in data-driven organizations.

By completing this project and EX101x and EX102x, you can obtain the XSeries Data Analysis Verified Certificate. 

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The course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.

EX101x is for all of those struggling with data analysis. That crazy data collection from your boss? Megabytes of sensor data to analyze? Looking for a smart way visualize your data in order to make sense out of it? We’ve got you covered!

Using video lectures and hands-on exercises, we will teach you cutting-edge techniques and best practices that will boost your data analysis and visualization skills.

We will take a deep dive into data analysis with spreadsheets: PivotTables, VLOOKUPS, Named ranges, what-if analyses, making great graphs - all those will be covered in the first weeks of the course. After that, we will investigate the quality of the spreadsheet model, and especially how to make sure your spreadsheet remains error-free and robust.

Finally, once we have mastered spreadsheets, we will demonstrate other ways to store and analyze data. We will also look into how Python, a programming language, can help us with analyzing and manipulating data in spreadsheets.

EX101x is created using Excel 2013 and Windows. Most assignments can be made using another spreadsheet program and operating system as well, but we cannot offer full support for all configurations.

The goal of this course is to help you to overcome data analysis challenges in your work, research or studies. Therefore we encourage you to participate actively and to raise real data analysis problems that you face in our discussion forums. 

This course is part of the Data Analysis XSeries.

LICENSE
The course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.

Struggling with data at work? Wasting valuable time working in multiple spreadsheets to gain an overview of your business? Find it hard to gain sharp insights from piles of data on your desktop?

If you are looking to enhance your efficiency in the office and improve your performance by making sense of data faster and smarter, then this advanced data analysis course is for you.

If you have already sharpened your spreadsheet skills in EX101x Data Analysis: Take It to the MAX(), this course will help you dig deeper. You will learn advanced techniques for robust data analysis in a business environment. This course covers the main tasks required from data analysts today, including importing, summarizing, interpreting, analyzing and visualizing data. It aims to equip you with the tools that will enable you to be an independent data analyst. Most techniques will be taught in Excel with add-ons and free tools available online. We encourage you to use your own data in this course but if not available, the course team can provide.

This course is part of the Data Analysis XSeries. 

LICENSE

The course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.

Please note that the verified certificate option is not currently open for this course. Please enroll in the audit track and you will be emailed when the verified certificate option is open for enrollment.

Businesses, consumers, and societies leave behind massive amounts of data as a by-product of their activities. Leading-edge companies in every industry are using analytics to replace intuition and guesswork in their decision-making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insights and running controlled experiments to test hypotheses.

This course, part of the Analytics: Essential Tools and Methods MicroMasters program, prepares you to understand data and business analytics and become a leader in these areas in business organizations.

It covers the methodologies, algorithms, issues, and challenges related to analyzing business data. It will illustrate the processes of analytics by allowing you to apply business analytics algorithms and methodologies to real-world business datasets from finance, marketing, and operations. The use of real-world examples and cases places business analytics techniques in context and teaches you how to avoid the common pitfalls, emphasizing theimportance of applying proper business analytics techniques.

In addition to cases, this course features hands-on experiences with data collection, analysis, and visualization using Python programs and analytics software such as SAS.

This course includes a significant analytics project.

Many people talk about the promise of “big data” to health care. But how can the application of data analytics to big data actually improve health and health care? We will show that novel data analytics based solutions can result in better diagnosis, better care and better curing. This provides fertile ground for entrepreneurship and the development of new businesses.

In our course we’ll start from the very basics of data analytics, look at different real world approaches and help you to see entrepreneurial opportunities and develop a business plan.

We will cover three important fields:

• Health care expertise: We will present medical approaches to data and give an overview of challenges where big data based solutions have been developed to improve the efficiency and effectiveness in medicine.
• Data analytics: We’ll explain the basics of data mining within the context of a wide variety of health care settings, and the types of data and data analysis challenges that you will likely encounter in each. We’ll start with gathering the data, move on to classifying, analyzing and finally visualizing it.
• Entrepreneurship: You will learn how to assess when data sciences based improvements in health care represent entrepreneurial opportunities. The development of a rigorous business plan is used to help you make that assessment.

Participants with prior experience in the medical field will learn how novel data science applications can improve healthcare, create societal value and how to spot entrepreneurial opportunities.

Participants with experience in data science or mathematics will learn about medical approaches to data and why healthcare is an exciting area to apply and develop data analytics.

Participants interested in launching their startup will learn how big data solutions in health care can provide a solid basis to build great ventures.

Whatever your motivation to enrol in this course, we care about your project and your success - that’s why we will guide you through all parts of this learning journey step by step!

Enter now to see how you can engage in data driven innovation and make an impact on improving care, outcomes and the quality of life.

Is your data messy? Do you need to learn how to clean it up? In this computer science course, we will discuss the discipline of Data Quality Assurance and Data Quality Services (DQS). You will learn why your data needs cleansing, the capabilities and features of DQS, what a DQS solution looks likes and how data cleansing integrates with an Integration Services (SSIS) data flow. We will demonstrate a variety of critical data quality activities such as knowledge discovery, domain management, matching policies for the de-duplication of data, and administration topics covering installation, configuration and security.

This course is part of the Microsoft Professional Program Certificate in Data Science.

Demand for data science talent is exploding. Develop your career as a data scientist, as you explore essential skills and principles with experts from Duke University and Microsoft.

In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization taught alongside practical application oriented examples such as how to build a cloud data science solution using Microsoft Azure Machine Learning platform, or with R, and Python on Azure stack.

This course is part of the Microsoft Professional Program Certificate in Data Science.

Showcase the knowledge and skills you’ve acquired during the Microsoft Professional Program for Data Science, and solve a real-world data science problem in this program capstone project. The project takes the form of a challenge in which you will explore a dataset and develop a machine learning solution that is tested and scored to determine your grade.

Note: This course assumes you have completed the previous courses in the Microsoft Professional Program for Data Science. For details, go to https://academy.microsoft.com/en-us/professional-program/data-science.