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Advanced Analytics and Applications
COURSE

Advanced Analytics and Applications

INR 59
0.0 Rating
📂 Nasscom FutureSkills Prime

Description

Advanced analytical techniques including predictive analytics, prescriptive analytics, real-time analytics, IoT analytics, and specialized big data applications across various industries.

Learning Objectives

Students will implement advanced analytical techniques for complex business problems, develop predictive and prescriptive analytics solutions, build real-time analytics systems, create IoT and sensor data analytics applications, apply advanced analytics to industry-specific use cases, and integrate artificial intelligence with big data analytics for intelligent decision-making systems.

Topics (10)

1
Predictive Analytics and Forecasting

Advanced predictive modeling techniques including time series forecasting, regression analysis, and machine learning for business prediction and planning.

2
Prescriptive Analytics and Optimization

Advanced analytics techniques that provide actionable recommendations and optimal decision paths using mathematical optimization and simulation methods.

3
Real-time Stream Analytics

Real-time data processing and analytics for immediate insights from streaming data sources including sensors, transactions, and user interactions.

4
Geospatial Analytics and Location Intelligence

Spatial data analysis and location intelligence using geographic information systems and spatial analytics for business and government applications.

5
Fraud Detection and Anomaly Detection

Sophisticated fraud detection and anomaly detection systems using advanced analytics to identify suspicious patterns and protect against financial crimes.

6
Customer Analytics and Behavioral Analysis

Advanced customer analytics techniques for understanding customer behavior, preferences, and value to optimize marketing strategies and customer relationships.

7
IoT and Sensor Data Analytics

Specialized analytics for IoT and sensor data including edge computing, real-time processing, and machine-to-machine communication analytics.

8
Graph Analytics and Network Analysis

Advanced graph analytics for analyzing complex relationships, networks, and interconnected data structures in big data applications.

9
Recommendation Systems and Personalization

Advanced recommendation systems and personalization engines using machine learning and big data to provide personalized user experiences and increase engagement.

10
Industry-Specific Big Data Applications

Specialized big data applications tailored to specific industry requirements and use cases including compliance, regulation, and industry-specific challenges.