Description
Data Science with R Training lets you gain expertise in Machine Learning Algorithms like K-MeansClustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Trainingencompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introductionto Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases onMedia, Healthcare, Social Media, Aviation and HR. CurriculumIntroduction to Data ScienceLearning Objectives - Get an introduction to Data Science in this module and see how Data Sciencehelps to analyze large and unstructured data with different tools. Topics: What is Data Science? What does Data Science involve?Era of Data Science Business Intelligence vs Data ScienceLife cycle of Data Science Tools of Data ScienceIntroduction to Big Data and Hadoop Introduction to RIntroduction to Spark Introduction to Machine LearningStatistical InferenceLearning Objectives - In this module, you will learn about different statistical techniques andterminologies used in data analysis. Topics: What is Statistical Inference? Terminologies of StatisticsMeasures of Centers Measures of SpreadProbability Normal DistributionBinary DistributionData Extraction, Wrangling and ExplorationLearning Objectives - Discuss the different sources available to extract data, arrange the data instructured form, analyze the data, and represent the data in a graphical format. Topics: Data Analysis Pipeline What is Data ExtractionTypes of Data Raw and Processed DataData Wrangling Exploratory Data AnalysisVisualization of DataIntroduction to Machine LearningLearning Objectives - Get an introduction to Machine Learning as part of this module. You willdiscuss the various categories of Machine Learning and implement Supervised Learning Algorithms. Topics: What is Machine Learning? Machine Learning Use-CasesMachine Learning Process Flow Machine Learning CategoriesSupervised Learning algorithm: LinearRegression and Logistic Regression
