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Our Courses
TOEFL Reading and Listening Sections Skills Mastery
This course prepares non-native speakers of English to take the reading and listening sections of the TOEFL iBT exam. This course takes a close look at every type of listening and reading question that you may encounter on the test and provides effective strategies for tackling each type. Expanding your vocabulary, a critical part of improving your overall skills in English, is another focal point of this course. This course also teaches how to best practice and prepare for test day as well as how to manage your time and perform optimally during the exam.
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Course by
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Self Paced
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8 hours
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English
Transformation of the Global Food System
The UN predicts we will be 9-10 billion people on Earth in 2050. Providing so many people with nutritious foods is a massive challenge and one that cannot be met by simply upscaling current practices regarding food production and consumption. Providing humanity with nutritional food is at the center of all decisions related to sustainable development. Agriculture is responsible for 80% of global deforestation. The food systems release 29% of global greenhouse gasses.
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Course by
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Self Paced
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12 hours
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English
TOEFL Test-Taking Strategies
This course prepares non-native speakers of English to take the TOEFL iBT exam by providing helpful tips and proven techniques for successfully completing the reading, listening, speaking, and writing sections of the iBT. In this course, you will learn a variety of strategies such as note-taking, using templates, and analyzing speech patterns, and you will review many sample questions and responses. This course also teaches how to best practice and prepare for test day as well as how to manage your time and perform optimally during the exam.
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Course by
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Self Paced
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8 hours
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English
Scikit-Learn For Machine Learning Classification Problems
Hello everyone and welcome to this new hands-on project on Scikit-Learn Library for solving machine learning classification problems. In this project, we will learn how to build and train classifier models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means.
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Course by
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Self Paced
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2 hours
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English
TOEFL Speaking and Writing Sections Skills Mastery
This course prepares non-native speakers of English to take the speaking and writing sections of the TOEFL iBT exam. This course explains the difference between the integrated tasks and independent tasks in the speaking and writing sections of the iBT and provides effective strategies for tackling each task. For each type of prompt, you will learn how to best plan your responses, which is a key step to providing well-formed and organized answers. This course also teaches how to best practice and prepare for test day as well as how to manage your time and perform optimally during the exam.
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Course by
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Self Paced
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8 hours
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English
Choosing an Objective for a Facebook Ad Campaign
By the end of this project, you will be able to choose the right Facebook Ad Campaign Objective for your brand using the Facebook Business Manager’s “Ads Manager”. Throughout this project, you will be able to identify all 11 types of Facebook Ad Campaign objectives and the difference between them.
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Course by
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Self Paced
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2 hours
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English
Practical Guide to Navigating Professional Relationships
This is Course 5 in the Salesforce Sales Development Representative Professional Certificate. In order to successfully complete the course, please ensure you have taken Course 1: Groundwork for Success in Sales Development, Course 2: Foundations for Interviewing with Confidence, 3: Conversational Selling Playbook for SDRs, and 4: Boosting Productivity through the Tech Stack. In this course, you’ll develop ‘power’ skills that are often overlooked but can actually determine success in your role.
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Course by
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Self Paced
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20 hours
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English
Wood Science: Beyond Building
The central question of this course: “why study wood?” If “why study wood” is the question, one answer would be that it is the only raw material available to us that is truly renewable in human life span terms. Wood is as important to society today as it ever was, despite the development of many man-made substitute materials, changing resource availability, and the changing needs of society.
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Course by
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Self Paced
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11 hours
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English
Advanced Interviewing Techniques
People interviewing for jobs today often fail because they are using yesterday's strategies. Recruiting technology has become more sophisticated, and the best employers are constantly changing the way interviews are done. This course gives you detailed strategies for handling tough competency-based, or behavioral, interviews so that you can communicate the knowledge, skills, and abilities that you have and that employers demand. You will be able to: 1. Identify what the hiring organization is looking for in using behavioral interviewing techniques. 2. List the steps in the S.T.A.R.
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Course by
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Self Paced
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21 hours
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English
Regression Analysis
The "Regression Analysis" course equips students with the fundamental concepts of one of the most important supervised learning methods, regression. Participants will explore various regression techniques and learn how to evaluate them effectively. Additionally, students will gain expertise in advanced topics, including polynomial regression, regularization techniques (Ridge, Lasso, and Elastic Net), cross-validation, and ensemble methods (bagging, boosting, and stacking).
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Course by
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Self Paced
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40 hours
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English
Modeling Time Series and Sequential Data
In this course you learn to build, refine, extrapolate, and, in some cases, interpret models designed for a single, sequential series. There are three modeling approaches presented. The traditional, Box-Jenkins approach for modeling time series is covered in the first part of the course. This presentation moves students from models for stationary data, or ARMA, to models for trend and seasonality, ARIMA, and concludes with information about specifying transfer function components in an ARIMAX, or time series regression, model. A Bayesian approach to modeling time series is considered next.
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Course by
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Self Paced
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11 hours
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English
Scikit-Learn to Solve Regression Machine Learning Problems
Hello everyone and welcome to this new hands-on project on Scikit-Learn for solving machine learning regression problems. In this project, we will learn how to build and train regression models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means. This project is practical and directly applicable to many industries.
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Course by
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Self Paced
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3 hours
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English
Implementing RPA with Cognitive Automation and Analytics
The explosive growth of Robotic Process Automation (RPA) in the past few years has created a tremendous demand to learn and become skilled in this exciting technology. This four course Specialization is designed to introduce RPA, provide a foundation of the RPA lifecycle--from design to bot deployment--and implement RPA with cognitive automation and analytics. Experienced and novice users and developers of RPA will all benefit from completing this Specialization.
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Course by
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Self Paced
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English
Machine Learning: Theory and Hands-on Practice with Python
In the Machine Learning specialization, we will cover Supervised Learning, Unsupervised Learning, and the basics of Deep Learning. You will apply ML algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Starting with supervised learning, we will cover linear and logistic regression, KNN, Decision trees, ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Then we turn our attention to unsupervised methods, including dimensionality reduction techniques (e.g., PCA), clustering, and recommender systems.
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Course by
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Self Paced
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English
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 hours
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English
Building and Managing Superior Skills
Designed with the modern professional in mind, our skills management course is your transformative journey towards career success. This course offers key insights into strategies for skills-based hiring, enabling you to identify and analyze job-specific skills in your chosen field. You'll establish a systematic process for auditing and advancing your skills, boosting your professional agility. Throughout this course, you'll become familiar with Generative AI as a forward-thinking tool for skills assessment, self-assessment, and development.
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Course by
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Self Paced
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18 hours
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English
Machine Learning: Classification
Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank.
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Course by
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Self Paced
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21 hours
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English