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AKTU Data Analytics and Visualization Lab (BCDS551) Syllabus PDF – B.Tech 3rd Year
Data Analytics and Visualization Lab BCDS551
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- Semester 5
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Official AKTU syllabus of Data Analytics and Visualization Lab (BCDS551) for B.Tech 3rd Year – 1 credits, L-T-P 0-0-2. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Data Analytics and Visualization Lab
Download PDFBCDS551 · 1 credits · L-T-P 0-0-2
Course Outcomes
At the end of course, the student will be able to
| CO 1 | Implement numerical and statistical analysis on various data sources | K 3 |
| CO 2 | Apply data preprocessing and dimensionality reduction methods on raw data | K 3 |
| CO 3 | Implement linear regression technique on numeric data for prediction | K 3 |
| CO 4 | Execute clustering and association rule mining algorithms on different datasets | K 3 |
| CO 5 | Implement and evaluate the performance of KNN algorithm on different datasets | K , K 3 4 |
Course Content
- To get the input from user and perform numerical operations (MAX, MIN, AVG, SUM, SQRT, ROUND) using in R.
- To perform data import/export (.CSV, .XLS, .TXT) operations using data frames in R.
- To get the input matrix from user and perform Matrix addition, subtraction, multiplication, inverse transpose and division operations using vector concept in R.
- To perform statistical operations (Mean, Median, Mode and Standard deviation) using R.
- To perform data pre-processing operations i) Handling Missing data ii) Min-Max normalization
- To perform dimensionality reduction operation using PCA for Houses Data Set
- To perform Simple Linear Regression with R.
- To perform K-Means clustering operation and visualize for iris data set
- Learn how to collect data via web-scraping, APIs and data connectors from suitable sources as specified by the instructor.
- Perform association analysis on a given dataset and evaluate its accuracy.
- Build a recommendation system on a given dataset and evaluate its accuracy.
- Build a time-series model on a given dataset and evaluate its accuracy.
- Build cartographic visualization for multiple datasets involving various countries of the world; states and districts in India etc.
- Perform text mining on a set of documents and visualize the most important words in a visualization such as word cloud. Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner It is also suggested that open source tools should be preferred to conduct the lab (R, Python etc. )
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