#1 Best Data Analytics course training in Delhi NCR with Placement Assistance

Introduction to Data Analytics

• Data Analytics Overview

• Data Collection and Preparation

• Data Exploration and Visualization

• Descriptive and Predictive Analytics

• Machine Learning Algorithms

Data Exploration and Visualization

• Data Collection

• Data Cleaning

• Exploratory Data Analysis

• Data Visualization

• Interpretation of Results

Data Cleaning and Preprocessing

• Data Acquisition

• Data Validation

• Data Transformation

• Data Normalization

• Data Imputation

Predictive Modeling

• Types of Predictive Modeling

• Data Pre-processing

• Model Building

• Model Evaluation

• Model Deployment

Machine Learning Algorithms

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Deep Learning

• Natural Language Processing

Model Evaluation and Selection

• Cross Validation

• Bias-Variance Tradeoff

• Overfitting and Underfitting

• Model Selection

• Model Performance Metrics

Time Series Analysis

• Introduction to Time Series Analysis

• Components of Time Series

• Time Series Decomposition

• Forecasting Time Series

• Time Series Modeling

Big Data Analysis

• Introduction to Big Data

• Data Collection and Storage

• Data Cleaning and Preprocessing

• Data Visualization

• Machine Learning Algorithms

Text Mining and Natural Language Processing

• Introduction to Text Mining

• Text Pre-Processing

• Text Representation

• Text Classification

• Text Clustering

Data Sources

• Primary Data Sources

• Secondary Data Sources

• Structured Data Sources

• Unstructured Data Sources

• External Data Sources

Data Acquisition

• Data Acquisition Strategies

• Data Acquisition Techniques

• Data Acquisition Tools

• Data Acquisition Process

• Data Acquisition Challenges

Data Cleaning

• Identifying and Handling Missing Values

• Formatting and Standardizing Data

• Data Normalization

• Data Transformation

• Outlier Detection and Removal

Data Transformation

• Data Extraction

• Data Cleaning

• Data Transformation

• Data Integration

• Data Visualization

Data Visualization

• Data Sources

• Data Cleaning

• Data Transformation

• Data Aggregation

• Data Sampling

Data Exploration

• Univariate Analysis

• Bivariate Analysis

• Multivariate Analysis

• Data Visualization

• Data Transformation

Data Visualization

• Types of Visualizations

• Exploratory Visualization Techniques

• Data Exploration and Visualization

• Visualizing Multivariate Data

• Visualizing Time Series Data

Descriptive Statistics

• Types of Descriptive Statistics

• Measures of Central Tendency

• Measures of Dispersion

• Skewness and Kurtosis

• Graphical Representation of Data

Inferential Statistics

• Descriptive Statistics

• Data Visualization

• Probability Distributions

• Hypothesis Testing

• Correlation and Regression Analysis

Data Mining Techniques

• Descriptive Statistics

• Data Visualization

• Data Transformation

• Outlier Detection

• Dimensionality Reduction

Regression Analysis

• Types of Regression

• Assumptions of Regression

• Correlation and Covariance

• Residual Analysis

• Model Building and Selection

Time Series Analysis

• Time Series Decomposition

• Autocorrelation and Partial Autocorrelation

• Seasonal Decomposition

• Time Series Forecasting

• Outlier Detection

Machine Learning Algorithms

• Univariate Analysis

• Bivariate Analysis

• Multivariate Analysis

• Dimensionality Reduction

• Data Visualization

Introduction to Statistics

• Descriptive Statistics

• Probability Distributions

• Estimation and Hypothesis Testing

• Regression Analysis

• Time Series Analysis

Descriptive Statistics

• Measures of Central Tendency

• Measures of Dispersion

• Skewness and Kurtosis

• Box Plots

• Correlation and Regression

Probability Theory

• Sample Space and Events

• Probability Axioms

• Conditional Probability

• Bayes' Theorem

• Random Variables

Statistical Inference

• Descriptive Statistics

• Probability Distributions

• Estimation Theory

• Hypothesis Testing

• Regression Analysis

Regression Analysis

• Simple Linear Regression

• Multiple Linear Regression

• Logistic Regression

• Polynomial Regression

• Stepwise Regression

Multivariate Analysis

• Multivariate Regression

• Factor Analysis

• Discriminant Analysis

• Canonical Correlation

• Cluster Analysis

Time Series Analysis

• Autoregressive Models

• Moving Average Models

• ARIMA Modeling

• Seasonal ARIMA Modeling

• Forecasting with Time Series Analysis

Experimental Design

• Introduction to Experimental Design

• Types of Experimental Design

• Factors Influencing Experimental Design

• Analysis of Experimental Design

• Applications of Experimental Design

Machine Learning Algorithms

• Linear Regression

• Logistic Regression

• Decision Trees

• Support Vector Machines

• Naive Bayes Classifier

Model Evaluation and Selection

• Bias-Variance Tradeoff

• Cross-Validation

• Regularization

• Model Selection

• Model Performance Metrics

Introduction to Machine Learning

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Deep Learning

• Natural Language Processing

Supervised Learning

• Regression

• Decision Trees

• Naive Bayes

• Support Vector Machines

• K-Nearest Neighbors

Unsupervised Learning

• Clustering

• Dimensionality Reduction

• Association Rule Mining

• Anomaly Detection

• Feature Selection

Linear Regression

• Introduction to Linear Regression

• Assumptions of Linear Regression

• Simple Linear Regression

• Multiple Linear Regression

• Model Evaluation and Diagnostics

Logistic Regression

• Introduction to Logistic Regression

• Logistic Regression Model

• Estimating Coefficients

• Assessing the Model

• Multiclass Logistic Regression

Decision Trees

• Introduction to Decision Trees

• Building Decision Trees

• Pruning Decision Trees

• Advantages and Disadvantages of Decision Trees

• Applications of Decision Trees

Support Vector Machines

• Introduction to Support Vector Machines

• Kernel Functions

• Support Vector Classification

• Support Vector Regression

• Optimization Techniques

Naive Bayes

• Bayes Theorem

• Conditional Probability

• Naive Bayes Classifier

• Naive Bayes Algorithm

• Applications of Naive Bayes

Clustering

• K-Means Clustering

• Hierarchical Clustering

• Fuzzy C-Means Clustering

• Density-Based Clustering

• Model-Based Clustering

Dimensionality Reduction

• Principal Component Analysis

• Factor Analysis

• Singular Value Decomposition

• Independent Component Analysis

• Non-Negative Matrix Factorization

Ensemble Learning

• Bagging

• Boosting

• Random Forest

• Stacking

• Adaboost

Artificial Neural Networks

• Introduction to Artificial Neural Networks

• Activation Functions

• Training of Neural Networks

• Architectures of Neural Networks

• Applications of Neural Networks

Deep Learning

• Artificial Neural Networks

• Convolutional Neural Networks

• Recurrent Neural Networks

• Autoencoders

• Reinforcement Learning

Introduction to Data Visualization

• Types of Data Visualization

• Data Visualization Tools

• Data Visualization Techniques

• Data Visualization Best Practices

• Data Visualization Challenges

Types of Data Visualization

• Line Graphs

• Bar Graphs

• Pie Charts

• Heat Maps

• Scatter Plots

Exploratory Data Analysis

• Types of Visualizations

• Data Visualization Tools

• Data Visualization Techniques

• Data Visualization Best Practices

• Data Visualization Challenges

Data Visualization Tools

• Matplotlib

• Seaborn

• Tableau

• Plotly

• Bokeh

Data Visualization Techniques

• Introduction to Data Visualization

• Types of Data Visualization

• Data Visualization Tools

• Data Visualization Best Practices

• Data Visualization Challenges

Data Visualization Best Practices

• Types of Visualizations

• Design Principles

• Color Theory

• Chart Selection

• Storytelling with Data

Data Visualization Dashboards

• Introduction to Data Visualization

• Types of Data Visualization

• Creating Dashboards

• Designing Dashboards

• Dashboard Best Practices

Data Visualization Challenges

• Data Exploration

• Data Cleaning

• Data Representation

• Data Visualization Techniques

• Data Interpretation

Introduction to Data Communication

• Types of Data Communication

• Network Topology

• Protocols

• Data Transmission Modes

• Network Security

Data Network Topologies

• Point-to-Point Topology

• Bus Topology

• Star Topology

• Ring Topology

• Mesh Topology

Network Protocols

• TCP/IP

• HTTP

• FTP

• SMTP

• DHCP

Data Transmission

• Types of Data Transmission

• Analog and Digital Transmission

• Data Transmission Media

• Protocols for Data Transmission

• Data Transmission Security

Network Security

• Types of Network Security

• Network Security Protocols

• Network Security Architectures

• Network Security Threats

• Network Security Solutions

Network Management

• Network Topology

• Network Protocols

• Network Security

• Network Troubleshooting

• Network Monitoring

Wireless Communication

• Introduction to Wireless Communication

• Types of Wireless Communication

• Wireless Network Topologies

• Wireless Network Protocols

• Wireless Network Security

Introduction to Data Governance

• Definition of Data Governance

• Data Governance Framework

• Data Governance Roles and Responsibilities

• Data Governance Processes

• Data Governance Tools

Data Governance Framework

• Introduction to Data Governance

• Data Governance Principles

• Data Governance Processes

• Data Governance Tools

• Data Governance Best Practices

Data Governance Processes

• Data Governance Framework

• Data Quality Management

• Data Security and Privacy

• Data Access and Usage

• Data Metadata Management

Data Quality Management

• Data Quality Standards

• Data Quality Measurement

• Data Quality Assurance

• Data Quality Improvement

• Data Quality Auditing

Data Security and Privacy

• Data Security Principles

• Data Privacy Regulations

• Data Access Control

• Data Encryption

• Data Auditing and Monitoring

Metadata Management

• Introduction to Metadata Management

• Metadata Standards and Best Practices

• Metadata Repositories

• Metadata Interoperability

• Metadata Security and Privacy

Data Governance Automation Tools

• Introduction to Data Governance

• Data Governance Automation Tools

• Data Governance Frameworks

• Data Governance Best Practices

• Data Governance Implementation Strategies

Data Governance Best Practices

• Data Governance Principles

• Data Quality Management

• Data Security & Privacy

• Data Access & Usage Policies

• Data Stewardship & Ownership

Regulatory Compliance

• Data Quality

• Data Security

• Data Privacy

• Data Retention

• Data Accessibility

Data Governance in the Cloud

• Introduction to Data Governance in the Cloud

• Cloud Computing and Data Governance

• Data Security in the Cloud

• Data Quality and Compliance in the Cloud

• Data Governance Best Practices in the Cloud

Introduction to Big Data

• What is Big Data?

• Big Data Sources

• Big Data Storage

• Big Data Processing

• Big Data Visualization

Understanding Data Warehousing

• Introduction to Data Warehousing

• Data Warehousing Architecture

• Data Modeling in Data Warehousing

• ETL Process in Data Warehousing

• Data Warehousing Tools and Technologies

Exploring Hadoop and MapReduce

• Introduction to Hadoop

• Hadoop Architecture

• MapReduce Framework

• MapReduce Programming

• Hadoop Ecosystem Components

Working with NoSQL

• Introduction to NoSQL

• Types of NoSQL Databases

• Working with MongoDB

• Working with Cassandra

• Working with HBase

Data Analysis with R

• Introduction to Big Data

• Big Data Storage and Retrieval

• Data Mining with R

• Visualizing Big Data

• Big Data Analytics with R

Introduction to Machine Learning

• Types of Machine Learning

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Deep Learning

Advanced Machine Learning Techniques

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Deep Learning

• Natural Language Processing

Text Mining and Natural Language Processing

• Text Preprocessing

• Text Classification

• Text Clustering

• Text Summarization

• Text Mining Applications

Predictive Analytics

• Introduction to Predictive Analytics

• Machine Learning Algorithms

• Data Pre-processing

• Model Evaluation and Selection

• Predictive Model Deployment

Big Data Visualization

• Introduction to Big Data Visualization

• Data Visualization Tools

• Data Visualization Techniques

• Data Visualization Best Practices

• Data Visualization Challenges

Introduction to Advanced Data Analytics

• Descriptive Statistics

• Predictive Modeling

• Machine Learning

• Text Mining

• Time Series Analysis

Data Preprocessing and Feature Engineering

• Data Cleaning

• Data Transformation

• Feature Selection

• Feature Extraction

• Feature Scaling

Supervised Learning

• Regression Analysis

• Decision Trees

• Support Vector Machines

• Naive Bayes

• Ensemble Learning

Unsupervised Learning

• Clustering

• Dimensionality Reduction

• Association Rule Mining

• Anomaly Detection

• Recommender Systems

Model Evaluation and Model Selection

• Cross Validation

• Bias-Variance Tradeoff

• Regularization

• Hyperparameter Tuning

• Model Selection Criteria

Time Series Forecasting

• Introduction to Time Series Forecasting

• Components of Time Series

• Types of Time Series

• Time Series Modeling

• Time Series Forecasting Techniques

Natural Language Processing

• Text Preprocessing

• Text Classification

• Text Clustering

• Text Summarization

• Text Generation

Deep Learning

• Neural Networks

• Convolutional Neural Networks

• Recurrent Neural Networks

• Autoencoders

• Generative Adversarial Networks

Reinforcement Learning

• Markov Decision Process

• Temporal Difference Learning

• Q-Learning

• Policy Gradient Methods

• Deep Reinforcement Learning

Big Data Analytics

• Machine Learning

• Deep Learning

• Natural Language Processing

• Time Series Analysis

• Predictive Analytics