Professional Certificate in Data Science & Support Vector Machines
-- ViewingNowThe Professional Certificate in Data Science & Support Vector Machines is a comprehensive course that equips learners with vital data science skills. This program covers essential topics such as machine learning, statistical analysis, and predictive modeling using Support Vector Machines (SVMs).
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โข Introduction to Data Science: Defining data science, understanding its role in business decision making, and exploring the various disciplines that contribute to data science.
โข Data Preprocessing: Cleaning and transforming raw data into a format suitable for analysis, including data wrangling, data imputation, and data normalization.
โข Exploratory Data Analysis: Examining data to discover patterns, trends, and outliers, and to formulate hypotheses for further analysis.
โข Statistical Inference: Understanding and applying statistical methods to draw conclusions from data, including hypothesis testing and confidence intervals.
โข Machine Learning Fundamentals: Introduction to machine learning, including supervised and unsupervised learning, and various algorithms such as linear regression, logistic regression, and decision trees.
โข Support Vector Machines (SVMs): Introduction to SVMs, understanding their theoretical foundations, and applying SVMs to solve classification and regression problems.
โข SVM Optimization Techniques: Exploring various optimization techniques, including kernel functions, to improve SVM performance.
โข Evaluation Metrics for SVMs: Understanding the various evaluation metrics, such as accuracy, precision, recall, and F1 score, for assessing the performance of SVMs.
โข Real-World Applications of SVMs: Exploring real-world applications of SVMs, including image classification, natural language processing, and bioinformatics.
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