Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Practical Data Science with MATLAB
Do you find yourself in an industry or field that increasingly uses data to answer questions? Are you working with an overwhelming amount of data and need to make sense of it? Do you want to avoid becoming a full-time software developer or statistician to do meaningful tasks with your data? Completing this specialization will give you the skills and confidence you need to achieve practical results in Data Science quickly.
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Course by
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Self Paced
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الإنجليزية
Using Descriptive Statistics to Analyze Data in R
By the end of this project, you will create a data quality report file (exported to Excel in CSV format) from a dataset loaded in R, a free, open-source program that you can download. You will learn how to use the following descriptive statistical metrics in order to describe a dataset and how to calculate them in basic R with no additional libraries.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Introduction to Trading, Machine Learning & GCP
In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks.
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Using Machine Learning in Trading and Finance
This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Introduction to Predictive Modeling
Welcome to Introduction to Predictive Modeling, the first course in the University of Minnesota’s Analytics for Decision Making specialization. This course will introduce to you the concepts, processes, and applications of predictive modeling, with a focus on linear regression and time series forecasting models and their practical use in Microsoft Excel.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
RStudio for Six Sigma - Process Capability
Welcome to RStudio for Six Sigma - Process Capability. This is a project-based course which should take under 2 hours to finish.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Introduction to Statistics in Python
In this project, learners will get a refresher of introductory statistics, learn about different python libraries that can be used to run statistical analysis, and create visualizations to represent the results. By the end of the project, the learners will import a real world data set, run statistical analysis to find means, medians , standard deviations, correlations, and other information of the data. The learners will also create distinct graphs and plots to represent the data.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Statistical Analysis using Python Numpy
By the end of this project you will use the statistical capabilities of the Python Numpy package and other packages to find the statistical significance of student test data from two student groups.
The T-Test is well known in the field of statistics. It is used to test a hypothesis using a set of data sampled from the population. To perform the T-Test, the population sample size, the mean, or average, of each population, and the standard deviation are all required. These will all be calculated in this project.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Reinforcement Learning for Trading Strategies
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Statistics for Marketing
This course takes a deep dive into the statistical foundation upon which marketing analytics is built. The first part of this course will help you to thoroughly understand your dataset and what the data actually means. Then, it will go into sampling including how to ask specific questions about your data and how to conduct analysis to answer those questions.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Predictive Modeling and Machine Learning with MATLAB
In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Exploratory Data Analysis with MATLAB
In this course, you will learn to think like a data scientist and ask questions of your data. You will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. You will learn to use MATLAB to automatically generate code so you can learn syntax as you explore.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Data Processing and Feature Engineering with MATLAB
In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB to lay the foundation required for predictive modeling. This intermediate-level course is useful to anyone who needs to combine data from multiple sources or times and has an interest in modeling. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Investments I: Fundamentals of Performance Evaluation
In this course, we will discuss fundamental principles of trading off risk and return, portfolio optimization, and security pricing. We will study and use risk-return models such as the Capital Asset Pricing Model (CAPM) and multi-factor models to evaluate the performance of various securities and portfolios. Specifically, we will learn how to interpret and estimate regressions that provide us with both a benchmark to use for a security given its risk (determined by its beta), as well as a risk-adjusted measure of the security’s performance (measured by its alpha).
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Course by
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Self Paced
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26 ساعات
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الإنجليزية