Certificate in Machine Learning for Data Science
-- ViewingNowThe Certificate in Machine Learning for Data Science is a crucial course designed to meet the increasing industry demand for skilled data scientists. This program empowers learners with essential skills in machine learning, a subfield of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed.
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• Introduction to Machine Learning: Principles and applications of machine learning, differentiating between supervised, unsupervised, and reinforcement learning.
• Data Preprocessing: Data cleaning, feature engineering, and data normalization techniques to prepare data for machine learning algorithms.
• Regression Analysis: Linear and logistic regression, identifying relationships between dependent and independent variables.
• Classification Techniques: Decision trees, random forests, k-nearest neighbors, and support vector machines.
• Clustering Algorithms: K-means, hierarchical clustering, and density-based spatial clustering.
• Dimensionality Reduction: Principal component analysis, singular value decomposition, and t-distributed stochastic neighbor embedding.
• Neural Networks and Deep Learning: Introduction to artificial neural networks, backpropagation, and deep learning techniques.
• Ensemble Learning: Boosting, bagging, and stacking techniques to improve machine learning performance.
• Evaluation Metrics: Accuracy, precision, recall, F1-score, ROC curves, and cross-validation strategies.
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- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- ThreeFourHoursPerWeek
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