Data science is a multidisciplinary field that uses techniques, tools, algorithms, systems to extract knowledge, actionable insights from data and apply knowledge to solve problems across a broad range of application domains. Digitalization is the key to the success of the business, which makes data science the most promising field in IT.
Students who have skills in Mathematics, Research, Data Analysis and Computer Science background. A Clear fundamental understanding of Programming concepts, SQL whereas hardcore programming skills are not needed.
☛ INTRODUCTION TO DATA SCIENCE
☛ DATA AND TOOLS
☛ DATA SCIENCE DEEP DIVE
☛ DATA
☛ STATISTICS & PROBABILITY
☛ SETUP
☛ DATA SOURCING, EXPLORATORY DATA ANALYSIS & READINESS
☛ DATA TRANSFORMATION/WRANGLING
☛ DATA SCIENCE CONCEPTS
☛ LINEAR REGRESSION
☛ POLYNOMIAL REGRESSION
☛ CLASSIFICATION
☛ LOGISTIC REGRESSION
☛ RANDOM FOREST
☛ NAÏVE BAYES THEOREM
☛ NLP FOR MACHINE LEARNING FEATURING
☛ SUPPORT VECTOR MACHINE
☛ GRADIENT BOOSTING MACHINE & XGBOOST
☛ K MEANS CLUSTERING ALGORITHM
☛ KERAS TENSOR FLOW – MLP DEEP LEARNING (NEURAL NETWORKS)
☛ H2O.AI
☛ SAMPLING & DIMENSION REDUCTION (DR)
☛ DEPLOYMENT OF MODEL TO PRODUCTION
☛ TABLEAU BASICS
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