Data Science Training

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About Course

The Data Science (DS) course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms, and illustrate impeccable Data Visualization by leveraging on ‘R’ capabilities.

Why Learn DS?

DS training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying (DS) job title with Big Data skills and expertise in R programming, Machine Learning, and Hadoop framework.

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What Will You Learn?

  • After the completion of the Data Science course, you should be able to:
  • 1. Gain insight into the 'Roles' played by a Data Scientist
  • 2. Analyze Big Data using R, Hadoop and Machine Learning
  • 3. Understand the Data Analysis Life Cycle
  • 4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
  • 5. Learn tools and techniques for data transformation
  • 6. Understand Data Mining techniques and their implementation
  • 7. Analyze data using machine learning algorithms in R
  • 8. Work with Hadoop Mappers and Reducers to analyze data
  • 9. Implement various Machine Learning Algorithms in Apache Mahout
  • 10. Gain insight into data visualization and optimization techniques
  • 11. Explore the parallel processing feature in R

Course Content

Data Science Training Videos

  • Data Science For Beginners
    00:00
  • Data Science Tutorial For Beginners
    00:00
  • What Is Data Science?
    00:00
  • Who is a Data Scientist?
    00:00
  • Data Analyst vs Data Engineer vs Data Scientist
    00:00
  • Data Scientist Job, Career & Salary
    00:00
  • Data Scientist Roles and Responsibilities
    00:00
  • Top 10 Reasons to Learn Data Science
    00:00
  • How to Become a Data Scientist
    00:00
  • Data Science Applications
    00:00
  • Introduction to R Programming
    00:00
  • Why R?
    00:00
  • Introduction to Functions in R
    00:00
  • Data Science with R
    00:00
  • Machine Learning with R
    00:00
  • Predictive Analytics Using R
    00:00
  • R vs Python
    00:00
  • What is Machine Learning?
    00:00
  • Machine Learning Algorithms
    00:00
  • Data Science Interview Questions
    00:00
  • Data Scientist Resume
    00:00
  • SQL For Data Science Tutorial
    39:01
  • Top 5 Algorithms used in Data Science
    00:00
  • K-Means Clustering Algorithm
    00:00
  • Decision Tree Algorithm & Analysis
    00:00
  • Naive Bayes Classifier Tutorial
    00:00
  • Random Forest Tutorial
    00:00
  • Linear Regression Algorithm
    00:00
  • Logistic Regression in R
    00:00
  • Linear Regression vs Logistic Regression
    00:00
  • Sentiment Analysis in R
    00:00
  • KNN Algorithm Using R
    00:00
  • Time Series In R
    00:00
  • Text Mining In R
    00:00
  • Support Vector Machine Tutorial Using R
    00:00
  • Jupyter Notebook Tutorial
    00:00
  • What is Deep Learning
    00:00
  • What Is Artificial Intelligence?
    00:00
  • Data Science and Machine Learning for Non Programmers
    00:00
  • Best Python Libraries For Data Science & Machine Learning
    00:00
  • Python Projects For Beginners
    00:00
  • Statistics And Probability Tutorial
    00:00
  • E & ICT Academy NIT Warangal Partners
    00:00
  • Introduction to Data Subsetting
    00:00
  • Association Rule Mining
    00:00
  • Understanding Hadoop Streaming
    00:00
  • Supervised Learning
    00:00
  • Problem Datasets In Data Science
    00:00
  • Introduction to RHDFS
    00:00
  • Introduction to RMR
    00:00
  • RHadoop – Integrating R with Hadoop
    00:00
  • Parallel Processing Tutorial
    00:00
  • Develop a Data Science Project
    00:00
  • Hill Climbing Algorithm
    00:00
  • Find-S Algorithm in Machine Learning
    00:00
  • The Future of AI
    00:00
  • What is Cognitive AI?
    00:00
  • Data Science Future Scope
    00:00
  • Predictive Analysis Using Python
    00:00
  • How to Learn Data Science in 2020
    00:00

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