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MOOC
With rapid globalization and proliferation of social media, businesses and organizations are in face of enormous communication challenges. How to communicate effectively on social media, how to manage social media data analysis as well as handling fake news are definitely at the top of the list.
By seeing challenge as opportunity, this course aims to unfold the communication challenges induced by the rise of social media in business corporations and most importantly, offer solutions to overcome these challenges. In addition, the course serves presents a vantage point to forge an interface of synergy between academics and practitioners to discuss and address global communication challenges. Participants can benefit from meaningful synergy between academics and practitioners as well as learning materials and meaningful multilateral discussions surrounding authentic communication cases and industrial practices engaging both instructors and participants. In sum, this course provides insights for business leaders, senior managerial members, and communication professionals by discussing the major communication challenges encountered by businesses around the world which in turn, helps the participants to advance their career in the ever-changing communication environment.
- Subjects:
- Communication
- Keywords:
- Social media Information technology -- Management
- Resource Type:
- MOOC
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MOOC
This data analytics course takes an interdisciplinary approach to demonstrate the data analytics process in the context of accounting and finance. The growing volume of both structured and unstructured data has pushed forward a more data-driven form of decision-making in accounting and finance. In order to keep up with the Big Data era advancements, accountants and finance professionals need to have a data analyst mindset to excel in their jobs. This course will illustrate different concepts of accounting and finance with the application of data analytics. It will not only help the learners to develop their skills to ask the right questions but also teach them how to master the data and use different tools like Excel and Tableau to analyze the data. In the end, the learners will be able to interpret the results and make their decisions effectively.
This course will use a simple framework that helps the learners to develop an analytical mindset. This framework (QDAR) has four major components:
1. Ask the right Q uestions to address an issue in accounting or finance contexts.
2. Understand the different data types and how to retrieve and clean D ata.
3. Conduct different data A nalyses to answer the questions
4. Communicate the R esults to the decision-makers using graphs, visualizations and reports.
The whole course will cover different aspects of the framework in conjunction with different types of analyses. There will be additional datasets for the verified learners through which they can practice what they have learned during the course.
- Subjects:
- Accounting and Finance
- Keywords:
- Accounting -- Data processing Finance -- Data processing
- Resource Type:
- MOOC
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Video
In 44 episodes, Adriene Hill teaches you Statistics! This course is based on the 2018 AP Statistics curriculum and introduces everything from basic descriptive statistics to data collection to hot topics in data analysis like Big Data and neural networks. By the end of the course, you will be able to: *Identify questions that can be answered using statistics *Describe patterns, trends, associations, and relationships in data both numerically and graphically *Justify a conclusion using evidence from data, definitions, or statistical inference *Apply statistical models to make inferences and predictions from data sets *Understand how statistics are used broadly in the world and interpret their meaning, like in newspapers or scientific studies Learning playlist
- Subjects:
- Mathematics and Statistics
- Keywords:
- Statistics
- Resource Type:
- Video
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Video
Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to make a "step-by-step" video that shows you exactly how it works.
- Course related:
- COMP4434 Big Data Analytics
- Subjects:
- Computing
- Keywords:
- Machine learning Computer algorithms
- Resource Type:
- Video
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MOOC
Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle. That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers. Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Big data
- Resource Type:
- MOOC
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MOOC
Everyday across the world, thousands of businesses are victimized by fraud. Who commits these bad acts? Why? And, how? In this course we are going to help you answer the questions: who commits fraud, why and how. We’ll also help you develop skills for catching them.
- Subjects:
- Accounting
- Keywords:
- Fraud -- Prevention Forensic accounting Fraud
- Resource Type:
- MOOC