Data Science Certification Training

Join this course to become an expert in Data Science and Analytics. You will be able to, explore, and visualize data, perform predictive analytics, and perform effectively to make informed business decisions. We offer hands-on sessions on R Cloudlab in various domains like retail, healthcare, insurance, and entertainment. You will become proficient in various data analytics with R language like techniques like predictive analytics and descriptive analytics techniques and learn about data exploration and data visualization.

• Get an introduction to Data Science in this Module and see how Data Science helps to analyze large and unstructured data with different tools.
• 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

• In this Module, you should learn about different statistical techniques and terminologies used in data analysis.
• 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
• Linear Regression
• Logistic Regression

• What is 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 Recommendation Types
• User-Based Recommendation
• Item-Based Recommendation
• Difference: User-Based and Item-Based Recommendation
• Recommendation Use-case

• 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