Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Personalised Medicine from a Nordic Perspective
The technical revolution has generated large amounts of data in healthcare and research, and a rapidly increasing knowledge about factors of importance for the individual’s health.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Supervised Learning and Its Applications in Marketing
Welcome to the Supervised Learning and Its Applications in Marketing course! Supervised learning is the process of making an algorithm to learn to map an input to a particular output. Supervised learning algorithms can help make predictions for new unseen data. In this course, you will use the Python programming language, which is an effective tool for machine learning applications. You will be introduced to the supervised learning techniques: regression and classification. The course will focus on the applications of these techniques in the domain of marketing.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Predictive Analytics: Basic Modeling Techniques
What is Predictive Analytics? These methods lie behind the most transformative technologies of the last decade, that go under the more general name Artificial Intelligence or AI. In this course, the focus is on the skills that will allow you to fit a model to data, and measure how well it performs. We will be doing enough data science so that you get hands-on familiarity with understanding a dataset, fitting a model to it, and generating predictions.
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Course by
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26
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الإنجليزية
Introduction to Astrophysics
Learn about the physical phenomena at play in astronomical objects and link theoretical predictions to observations.
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Course by
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18
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الإنجليزية
Physical and Advanced Side-Channel Attacks
Software-based and physical side-channel attacks have similar techniques. But physical attacks can observe properties and side effects that are usually not visible on the software layer. Thus, they are often considered the most dangerous side-channel attacks. In this course, we learn both about physical side-channel attacks but also about more advanced software-based side channels using prefetching and branch prediction. You will work with these attacks and understand how to mitigate them.
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Course by
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Self Paced
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الإنجليزية
PredictionX: Omens, Oracles & Prophecies
This course is an overview of divination systems, ranging from ancient Chinese bone burning to modern astrology.
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Course by
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الإنجليزية
PredictionX: Lost Without Longitude
Explore the history of navigation, from stars to satellites.
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Course by
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Self Paced
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60
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الإنجليزية
Introduction to Machine Learning: Supervised Learning
In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.
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Course by
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Self Paced
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40 ساعات
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الإنجليزية
Python Data Products for Predictive Analytics
Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego. This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy.
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Course by
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Self Paced
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الإنجليزية
Bayesian Statistics
This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution.
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Course by
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Self Paced
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الإنجليزية
Improving Your Statistical Questions
This course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Introduction to Business Analytics and Information Economics
This specialization targets learners who seek to understand the opportunities that data and analytics present for their organization and those interested in the value of and implications for data as an asset to their organization. Individuals who manage data and make decisions about how data can be leveraged in their organization will find this specialization of particular value. Businesses run on data, and data offers little value without analytics.
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Course by
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Self Paced
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الإنجليزية
Multiple Regression Analysis in Public Health
Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, you'll extend simple regression to the prediction of a single outcome of interest on the basis of multiple variables. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Deploy Models with TensorFlow Serving and Flask
In this 2-hour long project-based course, you will learn how to deploy TensorFlow models using TensorFlow Serving and Docker, and you will create a simple web application with Flask which will serve as an interface to get predictions from the served TensorFlow model.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Deploy a BigQuery ML Customer Churn Classifier to Vertex AI for Online Predictions
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will train, tune, evaluate, explain, and generate batch and online predictions with a BigQuery ML XGBoost model. You will use a Google Analytics 4 dataset from a real mobile application, Flood it!, to determine the likelihood of users returning to the application. You will generate batch predictions with your BigQuery ML model as well as export and deploy it to Vertex AI for online predictions.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Machine Learning for Telecom Customers Churn Prediction
In this hands-on project, we will train several classification algorithms such as Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Random Forest Classifier to predict the churn rate of Telecommunication Customers. Machine learning help companies analyze customer churn rate based on several factors such as services subscribed by customers, tenure rate, and payment method. Predicting churn rate is crucial for these companies because the cost of retaining an existing customer is far less than acquiring a new one.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Mining Quality Prediction Using Machine & Deep Learning
In this 1.5-hour long project-based course, you will be able to: - Understand the theory and intuition behind Simple and Multiple Linear Regression. - Import Key python libraries, datasets and perform data visualization - Perform exploratory data analysis and standardize the training and testing data. - Train and Evaluate different regression models using Sci-kit Learn library. - Build and train an Artificial Neural Network to perform regression. - Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, and adjusted R2. - Assess the performance of regressio
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
PredictionX: John Snow and the Cholera Epidemic of 1854
An in-depth look at the 1854 London cholera epidemic in Soho and its importance for the field of epidemiology.
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Course by
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الإنجليزية
Google Data Analytics
Prepare for a new career in the high-growth field of data analytics, no experience or degree required. Get professional training designed by Google and have the opportunity to connect with top employers. There are 483,000 open jobs in data analytics with a median entry-level salary of $92,000.¹ Data analytics is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision making. Over 8 courses, gain in-demand skills that prepare you for an entry-level job.
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Course by
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التعلم الذاتي
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الإنجليزية
Building Cloud Computing Solutions at Scale
With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find.
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Course by
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Self Paced
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الإنجليزية
Analyze Box Office Data with Seaborn and Python
Welcome to this project-based course on Analyzing Box Office Data with Seaborn and Python. In this course, you will be working with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? We try to answer these questions by way of exploratory data analysis (EDA) in this project and the next.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Communicating Data Science Results
Important note: The second assignment in this course covers the topic of Graph Analysis in the Cloud, in which you will use Elastic MapReduce and the Pig language to perform graph analysis over a moderately large dataset, about 600GB. In order to complete this assignment, you will need to make use of Amazon Web Services (AWS). Amazon has generously offered to provide up to $50 in free AWS credit to each learner in this course to allow you to complete the assignment.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Emergent Phenomena in Science and Everyday Life
Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future. However, there are some systems that defy this notion.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Basic Recommender Systems
The Basic Recommender Systems course introduces you to the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include the most important algorithms used to provide recommendations. You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of different recommender system alternatives. After completing this course, you'll be able to describe the requirements and objectives of recommender systems based on different application domains.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Bank Loan Approval Prediction With Artificial Neural Nets
In this hands-on project, we will build and train a simple deep neural network model to predict the approval of personal loan for a person based on features like age, experience, income, locations, family, education, exiting mortgage, credit card etc.
By the end of this project, you will be able to:
- Understand the applications of Artificial Intelligence and Machine Learning techniques in the banking industry
- Understand the theory and intuition behind Deep Neural Networks
- Import key Python libraries, dataset, and perform Exploratory Data Analysis.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية