About the Data Science Online Training
Form this Data Science Online Training you will able to learn all the Concepts of Data Science with real-time scenarios, live examples by real-time professionals.
Data Science is a new technology, which is basically used for apply critical analysis. It utilizes the potential and scope of Hadoop. It also helps fully in R programming and machine learning implementation. It is a blend of multiple technologies like data interface, algorithm. It helps to solve an analytical problem. Data Science provides a clear understanding of work in big data, analytical tool R. Also, provide the analyses big data. It gives the clear idea of understanding of data, transforming the data. Also, it helps is visualizing the data, exploratory analysis, understanding of null value. It used to impute the value with the help of different rules and logic.
What are the Course Objectives?
After completion of the Data Science Course at Naresh I technologies, you will be expertise and eligible for:
- Complete knowledge of Data Science
- Able to analyze big data
- Able to work in Data Mining
- Able to work on Statistic
- Learn how to use different tool like Tableau, Map Reduce
- Creation of decision tree
- Explore Big data concept
Who should go for this Course?
- Any IT experienced Professional who are interested to build their career in Development/ Data Scientist.
- Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ BCom College Students in any stream.
- Fresh Graduates.
The course can learn by any IT professional having basic knowledge of:
- Any Programming Language
Data Science Online Training Course Content:
Introduction to Data Science
- Introduction to Data Science
- Big Data
- Data Science Deep Dive
Intro to R Programming & Advanced R Programming
- Introduction to R
- R Programming Concepts
- Data Manipulation in R
- Data Import Techniques in R
- Exploratory Data Analysis (EDA) using R
- Data Visualization in R
Python Programming & Machine Learning
- Big Data and Hadoop Introduction
- Map Reduce Concepts
- Statistics basics
Machine Learning using R & Python
- ML Fundamentals
- Understanding Supervised and Unsupervised Learning Techniques
- Implementing Association rule mining
- Understanding Process flow of Supervised Learning Techniques
- Decision Tree Classifier
- Random Forest Classifier
- What is Random Forests
- Naive Bayes Classifier.
- Project Discussion
- Problem Statement and Analysis
- Linear Regression
- Logistic Regression
- Text Mining
- Sentimental Analysis
- Support Vector Machines
- Deep Learning
- Time Series Analysis
Apache Spark using Python
- Apache Spark
- Spark Core Architecture
- Spark Internals Detailed
- Intro to Spark Streaming
- Intro to Spark GraphX Programming
- Intro to Spark Mllib