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This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
What are the aims of this course? What learning disability is and isn't The facts of learning disabilities What barriers people with learning disabilities face Medical barriers Societal barriers How to support people with learning disabilities
The Generic Instructor Course trains future Instructors in the principles of adult learning. These skills can then be used to teach fellow healthcare professionals at a number of our courses, including ALS, EPALS and NLS.
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Leading People through Change: In-House Training Research shows that 70% of change initiatives fail in large organizations. The largest factor contributing to this failure rate is leadership - the inability to plan and lead people through change. In many change situations, tremendous focus is put on strategy, processes, and systems, while the issue of changing people's behavior is assumed it will 'just happen'. In this interactive course, you will learn why the people side of change is crucial. We will begin by understanding why and how people resist change, and how important it is to become strong and effective change champions. Next, we will focus on critical change management practices - creating our vision of the future state, planning for acceptance in our change audience and stakeholders, mitigating threats, and capitalizing on opportunities. We will use metrics to plan, show progress, and confirm success. Lastly, we will focus on the need to reinforce and sustain change, and to prevent relapse to old ways and methods. What you will Learn At the end of this program, you will be able to: Realize the nature of change and describe how resistance manifests in people Compare prevalent change models and categorize their similarities Identify and rate the skills, traits, and behaviors of effective change champions Envision the future state and assess stakeholders Plan for change communication, training, and risks Evaluate change effectiveness using feedback and metrics Develop reinforcement practices for benefits and communication Foundation Concepts What is Change? Resistance to Change Common Change Management Theories Becoming a Change Champion Plan Envisioning the future state Planning for people Change management plan Do Change communication Training Piloting Risks Study Feedback Metrics Variance analysis Act Benefits realization Change sustainment Reinforcement messaging and communications