Data Scientist

CRAVE-SOFT Technologies institute of Data Science certification training lets you master in deploying R Statistical computing, machine learning algorithms, data analysis, enabling you to work on real-world projects and case studies. You will learn business analytics, Time series analysis and more.

This is a complete Data Science boot camp specialization training course which provides the detailed learning in data science, data acquisition, project life cycle, data analytics, analysis, machine learning and statistical methods. You will gain the know-how to arrange Recommenders using data transformation, data analysis, experimentation, and evaluation.

Our CRAVE-SOFT Technologies institute provides the best Data Science training by our highly professional and certified trainers. The systems and processes to extract knowledge or insights from detaining various forms is an interdisciplinary field, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, machine learning, data mining, and predictive analytics, like Knowledge Discovery in Databases. We do corporate training’s and help the companies to train their employees. And resolve queries of the clients by providing real-time support.

Highlights Data Science training: –

• Very in-depth course material with Real-Time Setups for each topic with its Solutions for Data Science Online Training.
• We provide Case studies for Data Science Training.
• Our Highly Qualified Trainers and Real Time Experts do the schedule session based on your comfort.
• We provide the Fast Track, Normal Track and Weekend Batches also for Data Science Training.
• We provide Cost Effective and Flexible Payment Schemes.

Who can join this course?

• Big Data Specialists, Business Analysts, and Business Intelligence professionals.
• Statisticians looking to improve their Big Data statistics skill.
• Developers wanting to learn Machine Learning (ML) Techniques.
• Information Architects looking to learn Predictive Analytics.
• Those looking to take up the roles of Data Scientist and Machine Learning Expert.

Module 1 : Statistics

• Data Science / Analytics – An introduction
  • What is Statistics
  • Statistical Methods
  • Applications
  • Types of Statistics – Descriptive & Inferential
  • Variables – Qualitative & Quantitative
• Basic Statistics
  • Measures of Central tendency
    • Mean , Median, Mode
  • Quantiles, Quartiles, percentile
  • Standard Deviation,Variance
  • Co-Variance
  • Coorelation
  • Central Limit Theorem
  • Measures of Dispersion
  • Skewness and Kurtosis
• Different types of Distributions
• Hypothesis,Parametric & Non – Parametric Tests
  • Sample and Population
  • Determine the Probability
  • Hypothesis – Null & Alternate
  • Scenarios in Hypothesis testing
  • Compare the Probability and Make Decision
  • IQR
  • Z Test
  • T-Test
  • Chi Square Test
  • F Test
  • Anova
• Probability

• • Standard Normal Distribution
  • Normal Distribution
  • Geometric Distribution
  • Poisson Distribution
  • Binomial Distribution
  • Parameters vs. Statistics
    

Module 2 : Python

                Module  2.1 : Python Programming
                Module  2.2 : Advanced Python
                Module  2.3 : Python for Data Analytics

Module 3 :  Artificial Intelligence – Machine Learning

• Introduction
• Supervised & Unsupervised Models
• Linear Regresion – Simple / Multiple and its associated concepts
  • R-Square – Coefficient of Determination
  • Mean Square Error
  • SST,SSE,SSR
• Polynomial Regression
• Logistic Regression
• KNN
• K Means
• SVM
• Bayesian network models
• Dimensionality Reduction – PCA
• Tree based models
  • Ensemble Approach
  • Bagging/Boosting
  • Decision Tree
  • Random Forests
• XG Boost