Turn To Coding

Data Analytics

Fees: Free

Duration: 10 Weeks

Days/Time: Lecture: Monday 7:00 pm - 9:30 pm

Cybersecurity

We've prepared exclusive interview pointers and questions bank for our registered students. You can access the questions bank using your student id and password. Currently, our question bank can be accessed via HanuInnoTech Mobile App or On-line. We've also published hard copy of question bank. Here is preview:

Healthcare Analytics: Healthcare Analytics enables integration of patient's Electronic Health Record (EHR) data and qualitative metrics engine. Other data sources include World Health Orginization (WHO) data and Social Sentiment Data.
Advertising Analytics: Advertising Analytics enables integration of Point of Sale (POS) data and Social Media Data. The other data sources include User social data and past behavior data.
Social Sentiment Analytics: Social Sentiment Analytics enables integration of Social Media Data and User Web Click through data.
Agriculture Analytics: Agriculture Analytics enables integration of Crop and or Dairy Cattle Data and real-time sensor data from the agriculture fields. The other data sources include pesticides data, sale data, and weather (Geo) data.
We've prepared exclusive interview pointers and questions bank for our registered students. You can access the questions bank using your student id and password. Currently, our question bank can be accessed via HanuInnoTech Mobile App or On-line. We've also published hard copy of question bank. Here is preview:

We've prepared exclusive interview pointers and questions bank for our registered students. You can access the questions bank using your student id and password. Currently, our question bank can be accessed via HanuInnoTech Mobile App or On-line.

Week 1 (Getting Started)

Introduction

  • Data Mining
  • Knowledge Discovery in Databases (KDD)

Week 2 (Large-scale file systems and MapReduce)

  • Large-scale file systems and MapReduce
  • Google File System
  • MapReduce

Week 3 (Classification: Decision Trees, Naïve Bayes, SVM)

  • Decision Trees
  • Naïve Bayes
  • SVM

Week 4 (Classification (cont’d): K-Nearest Neighborhood, Evaluation methods)

  • K-Nearest Neighborhood
  • Evaluation methods

Week 5 (Clustering)

  • Clustering
  • Clustering Approaches
  • Hierarchical clustering

Week 6 (Clustering (cont'd))

  • Dendrogram
  • Single-Linkage Clustering

Week 7 (Recommendation Systems

  • Content Based Systems
  • Collaborative filtering Systems
  • The Utility Matrix
  • The Long Tail
  • Cosine Similarity
  • High level architecture of a Content-based Recommender

Week 8 (Recommendation Systems (cont'd))

  • Collaborative Recommendation Systems
  • Jaccard Distance
  • Cosine Distance
  • Rounding Data
  • Normalize Data

Week 9 (Association Rules Class Association Rules Sequential Pattern Analysis))

  • Association Rule Mining
  • Market Basket Analysis
  • Apriori Algorithm
  • WEKA

Week 10 (Information Retrieval and Web Search Link Analysis - PageRank)

  • Information Retrieval (IR)
  • The simplified architecture of a search engine
  • Web Crawling
  • Search Engines - Google Architecture Overview
  • IR - Preprocessing the document collection
  • User Web Queries
    • Vector Space Model

Week 11 (Link Analysis - HITS, Spam, Spam Farms)

  • Links
  • Social Network Analysis
  • Centrality
  • Prestige
  • Page Rank Analysis
  • HITS

Week 12 (Real-time Analytics, IoT & IoE – Big Data Use Cases)

  • Industry Analysis

Week 13

  • Project