ABOUT THIS COURSE
In this course you will get an introduction to data analytics and ideas in the data scientist's mindset. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like R,Python, Spark, git, GitHub, R, and RStudio, Tableau, statistics, machine learning and many more.
COURSE OBJECTIVE
- To understand different types of statistical approaches of data analytics.
- Understand data and know how to extracts insights from it.
- Learn R, Python and Spark for data preparation and analytics.
- Learn Tableau for building beautiful visualization for story telling.
- Learn Bigdata basics and introduction to Hadoop.
- Work on subject based industry relevant case studies and assignments.
- Work on industry relevant real time data science project.
- Retail and Finance domain knowledge enrichment.
INTRODUCTION TO DATA SCIENCE
- What is data Science?
- Introduction. Importance of Data Science.
- Demand for Data Science Professional.
- Brief Introduction to Big data and Data Analytics. Lifecycle of data science.
- Tools and Technologies used in data Science.
- Business Intelligence vs Data Science.
- Role of a data scientist.
PROGRAMMING BASICS
- R programming
- Python programming
- Spark programming
INTRODUCTION TO STATISTICS
- Fundamentals of Math and Probability
- Descriptive Statistics
- Inferential Statistics
- Hypothesis Testing
- Hands on with assignment & case studies
UNDERSTANDING AND IMPLEMENTING MACHINE LEARNING
- Introduction to Machine Learning
- Linear Regression
- Logistic Regression
- Decision Trees and Supervised Learning
- Unsupervised Learning
- Introduction to Deep Learning
- Natural language Processing
APACHE SPARK ANALYTICS
- What is Spark
- Introduction to Spark RDD
- Introduction to Spark SQL and Dataframes using R-Spark for machine learning.
VISUALISATION
- Introduction to Tableau
- Connecting to data source
- Creating dashboard pages
- How to create calculated columns Different charts
PROJECT
- Real time analytics project with instructor guidance
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