# Data Science

Supreme IT learning Data Science training makes you an expert in building the applications by leveraging capabilities of Data transformation using Map Reduce (RMR), Random Forest Classifier, Integrating R with Hadoop using R, Sub-setting data. Etc… Course Curriculum Data Science Bascis Introduction to Data Science What makes a Data Scientist? AI & Machine Learning – […]

Supreme IT learning Data Science training makes you an expert in building the applications by leveraging capabilities of Data transformation using Map Reduce (RMR), Random Forest Classifier, Integrating R with Hadoop using R, Sub-setting data. Etc…

Course Curriculum

Data Science Bascis

Introduction to Data Science What makes a Data Scientist?

AI & Machine Learning – An Introduction.

Hands on Python

Basic Statistics with Python+Tensorflow& R

Measures of Central tendency Measures of Dispersion Skewness and Kurtosis

Linear Algebra Review

Hypothesis, Parametric and Non-Parametric Tests

Sample and Population Formulate the Hypothesis Select an Appropriate Test Choose level of Significance Calculate Test Statistics

Probability Theory

Hands onwith Python+Tensorflow.

Events and their Probabilities Rules of Probability Conditional Probability and Independence Distribution of a Random Variable

Hands on with Python+Tensorflow

Model & Cost function, Linear Regression with One Variable

Solving Linear, Logistic regression using Maximum Likelihood Estimation and Linear Regression

Hands on with Python+Tensorflow

Linear Regression with Multiple Variables

Logistic Regression with Multivariate Logistic Regression

Applications of Logistic Regression, the link to Linear Regression and Machine Learning

Hands on with Python+Tensorflow

Determine the Probability Compare the Probability and Make Decision

One Sample T-Test Two Independent Samples Tests

Paired T-test,Proportional Test

Non-Parametric One Sample Test

Chi Square,Test Z Test,F Test

Decision Trees with Case study

Understanding Decision tree

Decision Tree terminology

Hands on Python

Building decision Tree

Decision tree evaluation

Hands on Python

k-Nearest Neighbors and Generalization.

K Nearest Neighbours Algorithm for Classification with case study

Lazy Learning Notion

Computation of Distance Matrix

The Optimum K values .

Data Transformations as a Pre-Processing Phase

Model Building on Training Data Set

Model Validation on Testing Data Set Evaluation of Model Advantages & Disadvantages of KNN Models

Support Vector Machine Fundamentals

Hands on with Python+Tensorflow.

Linear Classifiers: Support Vector Machines

Multi-Class Classification

Kernelized Support Vector Machines

Cross-Validation

Hands on with Python+Tensorflow

Optimization in Python

Kernels Introduction

Visualization and dimensionality reduction

Principal Component Analysis (PCA)

Kernel PCA

Locally-Linear Embedding (LLE)

t-distributed Stochastic Neighbor Embedding (t-SNE)

Association rule learning,Apriori,Eclat

Neural Networks: Concept, Representation, Building, Learning Hands on with Python+Tensorflow

Building an ANN,

Evaluating the ANN,

Improving the ANN

Tuning the ANN

Activation functions used in ANNs.

Practice Test & Interview Questions

Supreme IT learning offers advanced Data Science,  interview questions and answers along with Data Science resume samples. Take a free sample practice test before appearing in the certification to improve your chances of scoring high.

Project

The aim of the project module is to let you have an idea of what a project is, problem statement, various approaches and solving algorithms.

Project Discussion

Problem Statement and Analysis

Various approaches to solve a Data Science Problem

Pros and Cons of different approaches and algorithms

The Course goes with the aim to understand key concepts about the fundamentals of data science, Data acquisition and Machine learning algorithms. In this training course, you gain the knowledge tools and techniques of Experimentation, Evaluation and Project Deployment, Data collection and data mining. You will get an in-depth understanding of the big data concepts and the responsibilities of a data scientist. This course has been designed in such a way that it is very easy for you to acquire and expand your data science skills quickly. So, you can start working in this field once you complete the training successfully.
Data Science is being used by most of the world’s top multinationals. Data Science professionals are earning very high salaries when compared with other technologies.With high demand and a number of job opportunities in this field, the following people will get benefited from this course Information Architects Data analysts Business analysts Freshers/Graduates keep to take up the role of a data scientist BI professionals
An in-depth knowledge on data science project which focuses on all the critical components of data science will be provided by our trainer. As a result, you can increase your visibility and increase your efficiency and draw real connections between different components of data science. You will also get the complete material covering all the aspects of this project.

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