Data Analytics (B.Tech)

Data analysis process, statistical modelling, mining data streams, frequent itemsets, clustering and visualisation.

6 महीनेअवधि 5Chapters29टॉपिक

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सिलेबस · पाठ्यक्रम

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01Unit 1: Introduction to Data Analytics and Lifecycle 6 टॉपिक

Sources and nature of data: structured, semi-structured, unstructured
Need of data analytics and analytic scalability
Analytic process, tools; analysis vs reporting
Applications of data analytics
Data analytics lifecycle: discovery, data preparation, model planning, model building, communicating results, operationalisation
Key roles in an analytics project

02Unit 2: Data Analysis Techniques 6 टॉपिक

Regression modelling and multivariate analysis
Bayesian modelling, inference and Bayesian networks
SVM and kernel methods
Time series analysis
Rule induction and neural networks
PCA, fuzzy logic and stochastic search methods

03Unit 3: Mining Data Streams 6 टॉपिक

Stream concepts, data model and architecture
Sampling data in a stream
Filtering streams: Bloom filter
Counting distinct elements: Flajolet-Martin
Estimating moments and DGIM for counting ones in a window
Decaying window, RTAP; sentiment analysis and stock market case studies

04Unit 4: Frequent Itemsets and Clustering 6 टॉपिक

Market basket model and frequent itemsets
Apriori algorithm
Handling large datasets in main memory and limited-pass algorithms
Hierarchical and K-means clustering
Clustering high-dimensional data: CLIQUE, PROCLUS
Clustering in non-Euclidean space and for streams

05Unit 5: Frameworks, Visualisation and R 5 टॉपिक

MapReduce, Hadoop, Pig, Hive, HBase, MapR
Sharding, NoSQL databases, S3 and HDFS
Visual data analysis and interaction techniques
Introduction to R: GUI, data import / export, data types
Descriptive statistics and exploratory data analysis in R

परिचय

आप यह कर पाएँगे

Classify data and explain the data analytics lifecycle and key roles
Apply regression, Bayesian, SVM, time series, neural network, PCA and fuzzy techniques to data
Explain stream data models and algorithms: sampling, Bloom filter, Flajolet-Martin, DGIM
Mine frequent itemsets with Apriori and apply hierarchical, K-means and high-dimensional clustering
Explain Hadoop, Pig, Hive, HBase, sharding and NoSQL for analytics
Perform exploratory data analysis and visualisation in R

यह किसके लिए है

B.Tech Information Technology students of Semester 6 (AKTU)
Students of other universities studying the same subject who want unit-wise coaching

आपको क्या चाहिए

Database Management System and basic statistics
Basic Python or R

सवाल

Which syllabus does the Data Analytics course follow?

It follows the AKTU (Dr. A.P.J. Abdul Kalam Technical University, Lucknow) B.Tech syllabus for Data Analytics. If your own university's syllabus differs, the centre follows your university syllabus.

Will this help in the university examination?

Yes. Teaching is unit-wise as per the AKTU scheme, with previous-year question practice, MCQ tests and doubt sessions before the semester exam.

Is this subject only theory?

The exam is theory and numericals, but algorithms such as Apriori, K-means and Bloom filters are also demonstrated in R / Python.