Data Science Training in Hebbal,RT Nagar Bangalore
Data Science Training In Hebbal
Data science is a kind of field which provides a good platform to know the various fields in the field of IT sector. It provides you the knowledge of Tableau, python, R etc. which is similar to the data mining. You can become a data scientist or serve the IT sector by becoming an expert in your interested field in data science. There is a training institute out there which will fill you up with confidence, make you an analytical thinker, and impart decisionmaking capacity and so on.
Advantages Of Data Science Training In Hebbal
Once you become a data science expert, there are a plethora of opportunities that open its way for you. Given below are some of the benefits of opting for one of the data science courses in Hebbal:
 Trainers with an experience of not less than 8 years will make students to see themselves in a better tomorrow.
 Good ambiance and advanced classes and labs make students devote and concentrate better onto studies.
 Projects and Internships to sharpen skills.
 Good learning package to have a grip upon important points.
 Projects handling make students to build selfconfidence, leadership quality, a good communicator.
One must get its hands on data science training by a professional institute so as to obtain the right amount of experience as well as the knowledge that is needed further in the industry.
Data Minax Institute For Data Science Training In Hebbal
Data Minax is a premier institute to obtain your data science training in Hebbal. They have a good bunch of trainers who will make you trained so that you can achieve the pioneer of this field. Their package and practice sessions help you to build a complete strategy to achieve your target. Here, every student is brilliant and hence, you’ll surely learn a lot from there and it will continuously push you towards getting a perfect point of success. The environment of this institution is quite amazing as you will work in advanced lab and computers and during the training hours that will make you more skilled day by day.
Core Features Of Data Science Training In Hebbal By Data Minax
Data Minax is the best data science training institute in Hebbal. Ambiance and facility provided by the institution are incomparable. It is a perfect platform to make yourself a good trained selfconfident and data science expert. There may be many top data science training institutes in Hebbal but Data Minax has some excellent features that make it a unique organization. Check out their extensive list of features:
 Experienced staff to make their students expert.
 Placements and Internships facility for a good stable future.
 Flexible training hours for the comfort of the students.
 Affordable fee structure.
 Advanced computers with 24×7 availability.
Thus, Data Science Training in Hebbal is the perfect gateway for the students who want to become the data scientist and make them reach their destination. Check out the curriculum and opt for this course for best results.
Course Features
 Lectures 130
 Quizzes 0
 Duration 1 hours
 Skill level All level
 Language English
 Students 12
 Assessments Yes

Part 1: Introduction to Data Science/Analytics
1. INTRODUCTION TO DATA MANAGEMENT
 i. Data Science – Brief
 Data Science Languages – Excel, SQL, Python & Tableau, R.,
 Data Preparation Techniques
 Sample Use Case
 2. STATISTICS AND EDA
 ii. Introduction to Statistics
 Population and Samples
 Descriptive vs Inferential Statistics
 Parameters vs Statistics
 Variable Classification
 Scale of Measurement
 Statistical Methods
 iii. Data Visualization
 Recognize difference between grouped and ungrouped data
 Construct Frequency Distribution
 Construction of bar diagram, column diagram, histogram
 frequency polygon, pie chart scatter plot, bubble chart
 iv. Exploratory Data Analysis
 Measure of Shapes of Data
 Measure of central tendency for grouped & ungrouped Data
 Measures of Variability for Grouped and Ungrouped Data
 Various Outlier & Missing value treatments in data preparation
 Relationship between variables
 Correlation and causation.

Part 2: Introduction to R/Python
 Installing Python & Anaconda
 Basic Data Types
 Lists, Tuples & Dictionary
 Introduction to Numpy
 Numpy arrays and operations
 DataFrames & Series
 Group By with Pandas
 Merging, Joining, Concatenating & Interleaving
 Pandas Operations
 Plots with matplotlib and Seaborn
 Preprocessing with dataset
 EDA
 Case Study

Part 3: Distributions & Sampling

Part 4: Hypothesis Testing

Advanced Analytics
Part 5: Machine Learning
 1. Predictive Analysis – I
 i. Linear Regression
 Nature of Regression Analysis
 Meaning of the term linear
 Linearity in variables
 Linearity in parameters
 Method of Ordinary Least Square
 The classical linear regression model
 Standard errors of least square estimates
 The coefficient of determination r ^2
 R square and adjusted r square
 Goodness of fit
 The normality assumption
 Hypothesis testing
 Testing the overall significance of a multiple regression – F test
 Multicollinearity assumptions
 Autocorrelation
 Case study : Housing dataset
 ii. Logistic Regression
 Introduction
 Dichotomous dependent variable
 Odds and Odds Ratios
 The Logit Model
 Weight of Evidence and Information value
 Creation of Dummy Variable
 Parameter Estimates
 Goodness of fit, Concordance and discordance
 confusion matrix
 Sensitivity, Specificity , Information Gain
 ROC curve
 Case study : Prediction of Loan Dataset.
 iii. Clustering
 Cluster analysis intuition
 Types of Clustering
 KMeans Clustering
 Case Study
 iv. Principle Component Analysis
 2. Predictive Analysis – II
 i. MODEL SELECTION AND ADVANCED REGRESSION
 ii. DECISION TREES
 Random Forest regression
 Bagging and boosting
 Gradient Boosting
 XGBoost
 iii. NEURAL NETWORKS
 iv. TIME SERIES
 Stationary and Non Stationary Time Series
 Importing and cleaning
 Plotting
 Moving Averages
 Prediction (Holt Winters Method, MA, Exponential Smoothing)
 ARMA model
 Case Study

Part 6: Big Data – Overview

Part 7 : Deep Learning & NLP Overview
 1. NATURAL LANGUAGE PROCESSING
 BASICS OF TEXT PROCESSING
 LEXICAL PROCESSING
 SYNTAX AND SEMANTICS
 OTHER PROBLEMS IN TEXT ANALYTICS
 2. DEEP LEARNING & NEURAL NETWORKS
 INFORMATION FLOW IN A NEURAL NETWORK
 TRAINING A NEURAL NETWORK
 CONVOLUTIONAL NEURAL NETWORKS
 Use CNN’s to solve complex image classification problems
 RECURRENT NEURAL NETWORKS
 Study LSTMs and RNN’s applications in text analytics
 CREATING AND DEPLOYING NETWORKS USING TENSORFLOW AND KERAS
 Build and deploy your own deep neural networks on a website, learn to use tensorflow API and Keras

Part 8: Industry/Capstone Projects (Optional)