On Demand Online Learning   

In this course, you will learn about the role of operations and how they are connected to other business functions in manufacturing and service-focused organizations. You will learn and practice the use of decision-making frameworks and techniques applicable at all levels, from management-level strategic decisions such as connecting process to the needs of various customer segments, to front-line tactical decisions such as choosing between ordering larger quantities vs. ordering more frequently.

You will be able to:

• Relate underlying principles to operations management frameworks and techniques
• Synthesize information to make strategic operations decisions
• Evaluate processes on different dimensions
• Apply analytical techniques for tactical operations decision

This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.

In this course, you will learn about the role of operations and how they are connected to other business functions in manufacturing and service-focused organizations. You will learn and practice the use of decision-making frameworks and techniques applicable at all levels, from management-level strategic decisions such as connecting process to the needs of various customer segments, to front-line tactical decisions such as choosing between ordering larger quantities vs. ordering more frequently.

You will be able to:

• Relate underlying principles to operations management frameworks and techniques
• Synthesize information to make strategic operations decisions
• Evaluate processes on different dimensions
• Apply analytical techniques for tactical operations decision

This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.

Taught by Rice University communication faculty from the Rice Center for Engineering Leadership (RCEL). This course covers core topics in oral communication: Communication strategy, content, data visualization, and delivery. You’ll learn key principles in
• Creating a communication strategy
• Developing a clear message and organizing persuasive content
• Creating strong visual support
• Presenting data effectively
• Presenting professionally and confidently
• Handling formal presentations, giving pitches, speaking extemporaneously, managing online presentations, and lowering
public speaking anxiety

Selected materials courtesy of Communication Faculty at Rice University - all rights reserved.

Taught by Rice University communication faculty from the Rice Center for Engineering Leadership (RCEL). This course covers core topics in oral communication: Communication strategy, content, data visualization, and delivery. You’ll learn key principles in
• Creating a communication strategy
• Developing a clear message and organizing persuasive content
• Creating strong visual support
• Presenting data effectively
• Presenting professionally and confidently
• Handling formal presentations, giving pitches, speaking extemporaneously, managing online presentations, and lowering
public speaking anxiety

Selected materials courtesy of Communication Faculty at Rice University - all rights reserved.

Organisations have changed and now, more than ever, personnel management is crucial to organisational success. In this course you’ll explore a range of concepts, theories and methodologies that will help you navigate and optimise your work environment. Via structured learning activities (video lectures, quizzes, discussion prompts and written assessments) you will be exposed to the latest best-practice leadership strategies to enable your employees to achieve more at work. You’ll examine case studies on advanced leadership strategies and be challenged to consider how these might apply to your own workplace. And you’ll discover that your ability to manage and lead people in a flatter, more team-driven context is now the key to organisational success. As the world continues to undergo dynamic change, this course will prepare you to be the one to lead your team and your organisation into the dynamic work environments of tomorrow.

Organisations have changed and now, more than ever, personnel management is crucial to organisational success. In this course you’ll explore a range of concepts, theories and methodologies that will help you navigate and optimise your work environment. Via structured learning activities (video lectures, quizzes, discussion prompts and written assessments) you will be exposed to the latest best-practice leadership strategies to enable your employees to achieve more at work. You’ll examine case studies on advanced leadership strategies and be challenged to consider how these might apply to your own workplace. And you’ll discover that your ability to manage and lead people in a flatter, more team-driven context is now the key to organisational success. As the world continues to undergo dynamic change, this course will prepare you to be the one to lead your team and your organisation into the dynamic work environments of tomorrow.

In this course you will focus on process improvement. You will learn how to set organizational priorities for continuous process improvement, how to execute process improvement projects, and how to sustain the initiative for continuous improvements.

You will be able to:

• Relate underlying principles to frameworks and techniques used for process improvement
• Synthesize information to make decisions for organizational initiatives and process improvement
• Apply analytical techniques for tactical decisions in a process improvement project

This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.

In this course you will focus on process improvement. You will learn how to set organizational priorities for continuous process improvement, how to execute process improvement projects, and how to sustain the initiative for continuous improvements.

You will be able to:

• Relate underlying principles to frameworks and techniques used for process improvement
• Synthesize information to make decisions for organizational initiatives and process improvement
• Apply analytical techniques for tactical decisions in a process improvement project

This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.

By the end of this project, you will be fluent in identifying and analyzing customer journeys for new products and services and in deriving opportunities from your analysis, thus generating positive results for your business venture. This project is designed to engage and harness your visionary and exploratory abilities. You will use proven models in strategy and product development with the Miro platform to explore and analyze these customer journeys. This is an important step for individuals or companies wanting to explore new products or services.

We will practice critically examining customer segments and products structures that affect the business. You will engage in evaluating, through examples and hands-on practice, making decisions on product orientation. Furthermore, you will assess whether to modify or keep the product structure when entering the market. You will be ready to take an entrepreneurial idea through a scientific and logical process, helping you validate your ideas for a new business or service.

This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. This course will cover Chapters 1-5 of the textbook “Python for Everybody”. Once a student completes this course, they will be ready to take more advanced programming courses. This course covers Python 3.

This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You'll also learn how to override built-in methods and how to create "inherited" classes that reuse functionality. You'll also learn about how to design classes. Finally, you will be introduced to the good programming habit of writing automated tests for their own code.

The course is best-suited for you if you are already familiar with Python fundamentals, which are covered in the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). It is optional to have taken the "Data Collection and Processing with Python" course (course 3 of the specialization), but knowledge of retrieving and processing complex nested data is helpful.

This is the fourth of five courses in the Python 3 Programming Specialization.

This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You'll also learn how to override built-in methods and how to create "inherited" classes that reuse functionality. You'll also learn about how to design classes. Finally, you will be introduced to the good programming habit of writing automated tests for their own code.

The course is best-suited for you if you are already familiar with Python fundamentals, which are covered in the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). It is optional to have taken the "Data Collection and Processing with Python" course (course 3 of the specialization), but knowledge of retrieving and processing complex nested data is helpful.

This is the fourth of five courses in the Python 3 Programming Specialization.

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.

This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables. You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results.

You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes.

Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.

This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables. You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results.

You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes.

Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!

Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems. Students completing this course will be able to:
• Explain the importance of statistical thinking in solving problems
• Describe the importance of data, and the steps needed to compile and prepare data for analysis
• Compare core methods for summarizing, exploring and analyzing data, and describe when to apply these methods
• Recognize the importance of statistically designed experiments in understanding cause and effect

Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems. Students completing this course will be able to:
• Explain the importance of statistical thinking in solving problems
• Describe the importance of data, and the steps needed to compile and prepare data for analysis
• Compare core methods for summarizing, exploring and analyzing data, and describe when to apply these methods
• Recognize the importance of statistically designed experiments in understanding cause and effect

In this course, we will apply the central concept and applications of Time Value of Money (TVM) to explore the structure and pricing of stocks and bonds at an introductory level. In this course, you will learn about bonds, different types of bonds (Zero Coupon bonds, Government bonds). You will learn about bond pricing calculations and see their direct connection to market data on bonds. You will also learn about stocks, and their pricing and valuation. You will learn about growth and dividend stocks and how to use market data.

After completing this course, you will have an understanding of the two fundamental and pervasive ways in which savers transfer money to governments and corporations. You will be able to apply all this knowledge to personal investing decisions and, importantly, these same tools and frameworks are applicable to corporate decisions.

This course is part of the four-course Foundational Finance for Strategic Decision Making Specialization.

In this course, we will apply the central concept and applications of Time Value of Money (TVM) to explore the structure and pricing of stocks and bonds at an introductory level. In this course, you will learn about bonds, different types of bonds (Zero Coupon bonds, Government bonds). You will learn about bond pricing calculations and see their direct connection to market data on bonds. You will also learn about stocks, and their pricing and valuation. You will learn about growth and dividend stocks and how to use market data.

After completing this course, you will have an understanding of the two fundamental and pervasive ways in which savers transfer money to governments and corporations. You will be able to apply all this knowledge to personal investing decisions and, importantly, these same tools and frameworks are applicable to corporate decisions.

This course is part of the four-course Foundational Finance for Strategic Decision Making Specialization.