Introduction to Data Science
Need for Data Scientists Foundation of Data Science What is Business Intelligence What is Data Analysis, Data Mining, and Machine Learning Analytics vs Data Science Value Chain Types of Analytics Lifecycle Probability Analytics Project Lifecycle Data Basis of Data Categorization Types of Data Data Collection Types Forms of Data and Sources Data Quality, Changes and Data Quality Issues, Quality Story What is Data Architecture Components of Data Architecture OLTP vs OLAP How is Data Stored? Big Data What is Big Data? 5 Vs of Big Data Big Data Architecture, Technologies, Challenge and Big Data Requirements Big Data Distributed
Data Science Course Online Payment: Rs 41, 300/- (Rs 35,000 + Rs 6,300 (18% GST))
Computing and Complexity Hadoop Map Reduce Framework Hadoop Ecosystem Data Science Deep Dive What is Data Science? Why are Data Scientists in demand? What is a Data Product The growing need for Data Science Large-Scale Analysis Cost vs Storage Data Science Skills Data Science Use Cases and Data Science Project Life Cycle & Stages Map-Reduce Framework Hadoop Ecosystem Data Acquisition Where to source data Techniques Evaluating input data Data formats, Quantity and Data Quality Resolution Techniques Data Transformation File Format Conversions
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Anonymization Intro to R Programming Introduction to R Business Analytics Analytics concepts The importance of R in analytics R Language community and eco-system Usage of R in industry Installing R and other packages Perform basic R operations using command line Usage of IDE R Studio and various GUI R Programming Concepts The datatypes in R and its uses Built-in functions in R Subsetting methods Summarize data using functions Use of functions like head(), tail(), for inspecting data Use-cases for problem solving using R Data Manipulation in R Various phases of Data Cleaning Functions used in Inspection Data Cleaning Techniques Uses of functions involved Use-cases for.
Data Cleaning using R Data Import Techniques in R Import data from spreadsheets and text files into R Importing data from statistical formats Packages installation for database import Connecting to RDBMS from R using ODBC and basic SQL queries in R Web Scraping Other concepts on Data Import Techniques Exploratory Data Analysis (EDA) using R What is EDA? Why do we need EDA? Goals of EDA Types of EDA Implementing of EDA Boxplots, cor() in R EDA functions Multiple packages in R for data analysis Some fancy plots Use-cases for EDA using.
