Data Science using R Certification Training

Description

Data Science Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR.

 

Data science is a "concept to unify statistics, data analysis and their related methods" to "understand and analyse actual phenomena" with data. Data Science Training employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science from the sub-domains of machine learning, classification, cluster analysis, data mining, databases, and visualization. The Data Science Certification Course enables you to gain knowledge of the entire life cycle of Data Science, analyse and visualise different data sets, different Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes.

 

Data Science Certification Training is designed by industry experts to make you a Certified Data Scientist. The Data Science course offers:

  • In-depth knowledge of Data Science Life Cycle and Machine Learning Algorithms
  • Comprehensive knowledge of various tools and techniques for Data Transformation
  • The capability to perform Text Mining and Sentimental analyses on text data and gain an insight into Data Visualization and Optimization techniques
  • The exposure to many real-life industry-based projects which will be executed in RStudio
  • Projects which are diverse in nature covering media, healthcare, social media, aviation and HR
  • Rigorous involvement of an SME throughout the Data Science Training to learn industry standards and best practices
DROP A QUERY

Agenda

  • What is Data Science?
  • What does Data Science involve?
  • Era of Data Science
  • Business Intelligence vs Data Science
  • Life cycle of Data Science
  • Tools of Data Science
  • Introduction to Big Data and Hadoop
  • Introduction to R
  • Introduction to Spark
  • Introduction to Machine Learning
  • What is Statistical Inference?
  • Terminologies of Statistics
  • Measures of Centers
  • Measures of Spread
  • Probability
  • Normal Distribution
  • Binary Distribution
  • Data Analysis Pipeline
  • What is Data Extraction
  • Types of Data
  • Raw and Processed Data
  • Data Wrangling
  • Exploratory Data Analysis
  • Visualization of Data
  • What is Machine Learning?
  • Machine Learning Use-Cases
  • Machine Learning Process Flow
  • Machine Learning Categories
  • Supervised Learning algorithm: Linear Regression and Logistic Regression
  • What are classification and its use cases?
  • What is Decision Tree?
  • Algorithm for Decision Tree Induction
  • Creating a Perfect Decision Tree
  • Confusion Matrix
  • What is Random Forest?
  • What is Navies Bayes?
  • Support Vector Machine: Classification
  • What is Clustering & its use cases
  • What is K-means Clustering?
  • What is C-means Clustering?
  • What is Canopy Clustering?
  • What is Hierarchical Clustering?
  • What is Association Rules & its use cases?
  • What is Recommendation Engine & it’s working?
  • Types of Recommendations
  • User-Based Recommendation
  • Item-Based Recommendation
  • Difference: User-Based and Item-Based Recommendation
  • Recommendation use cases
  • The concepts of text-mining
  • Use cases
  • Text Mining Algorithms
  • Quantifying text
  • TF-IDF
  • Beyond TF-IDF
  • What is Time Series data?
  • Time Series variables
  • Different components of Time Series data
  • Visualize the data to identify Time Series Components
  • Implement ARIMA model for forecasting
  • Exponential smoothing models
  • Identifying different time series scenario based on which different Exponential Smoothing model can be applied
  • Implement respective ETS model for forecasting
  • Reinforced Learning
  • Reinforcement learning Process Flow
  • Reinforced Learning Use cases
  • Deep Learning
  • Biological Neural Networks
  • Understand Artificial Neural Networks
  • Building an Artificial Neural Network
  • How ANN works
  • Important Terminologies of ANN’s

Certification & Exam

Once you have successfully submitted the Data Science Certification project, it will be reviewed by our expert panel. After a successful evaluation, you will be awarded with Data Science Expert Certificate.

Why Us

We are here to ensure you get heard 24/7, and to take care of every single questions and doubts you have. Our dedicated support team will provide you best in class round the clock customer support. Superior customer service is the hallmark of our company and we always go the extra mile to satisfy each of our customers whether an individual or a corporate client.

FREQUENTLY ASKED QUESTIONS


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