315326: Data Analytics Syllabus for Information Technology 5th Sem K Scheme MSBTE PDF

Data Analytics detailed Syllabus for Information Technology (IF), K scheme PDF has been taken from the MSBTE official website and presented for the diploma students. For Subject Code, Subject Name, Lectures, Tutorial, Practical/Drawing, Credits, Theory (Max & Min) Marks, Practical (Max & Min) Marks, Total Marks, and other information, do visit full semester subjects post given below.

For all other MSBTE Information Technology 5th Sem K Scheme Syllabus PDF, do visit MSBTE Information Technology 5th Sem K Scheme Syllabus PDF Subjects. The detailed Syllabus for data analytics is as follows.

Rationale

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
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Course Outcomes:

Students will be able to achieve & demonstrate the following COs on completion of course based learning

1. Elaborate the fundamental concepts of Data Analytics.
2. Apply appropriate statistical techniques to analyze and interpret complex Datasets.
3. Analyze numerical data by creating pivot table.
4. Represent data in terms of various types of charts.
5. Visualize the data using a Python library.

Unit I

Introduction to Data Analytics 1.1 Data Analytics: An Overview, Importance of Data Analytics 1.2 Types of Data Analytics: Descriptive Analysis, Diagnostic Analysis, Predictive Analysis, Prescriptive Analysis, Visual Analytics 1.3 Life cycle of Data Analytics, Quality and Quantity of data, Measurement 1.4 Data Types, Measure of central tendency, Measures of dispersion 1.5 Sampling Funnel, Central Limit Theorem, Confidence Interval, Sampling Variation

Suggested Learning Pedagogie
Presentations Lecture Using Chalk-Board Case Study

Unit II

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Unit III

Data Analytics with Excel 3.1 Excel Dashboard: Tables and Data Grids, Dynamic Filters and Controls, Trend Analysis and Forecasting 3.2 Pivot Tables: Creating a Pivot Table Specifying Pivot Table Data 3.3 Changing a Pivot Tables, Calculation Filtering and Sorting a Pivot Table 3.4 Creating a Pivot Chart, Grouping Items 3.5 Updating a Pivot Table, formatting a Pivot Table using Slicers

Suggested Learning Pedagogie
Presentations Hands-on Demonstration

Unit IV

Data Visualization 4.1 Creating a Simple Chart, Charting Non-Adjacent Cells 4.2 Creating a Chart Using the Chart Wizard, Modifying Charts, Moving an Embedded Chart, Sizing an Embedded Chart 4.3 Changing the Chart Type, Changing the Way Data is Displayed, Moving the Legend 4.4 Formatting Charts, Adding Chart Items, Formatting All Text, Formatting and Aligning Numbers, Formatting the Plot Area, Formatting Data Markers 4.5 Pie Charts, Creating a Pie Chart Moving the Pie Chart to its Own Sheet Adding Data Labels, Exploding a Slice of a Pie Chart

Suggested Learning Pedagogie
Presentations Hands-on Demonstration

Unit V

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
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List of Experiments:

1. * a. Calculate mean, median, and mode for a given dataset using Excel functions (AVERAGE, MEDIAN, MODE). * b. Calculate range, interquartile range (IQR), variance, and standard deviation using Excel functions (STDEV, VAR). * c. Calculate the correlation coefficient between two variables using the CORREL function
2. * a. Construct a box plot using the Insert Chart feature to identify the median, quartiles, and outliers of a dataset. * b. Perform a simple linear regression analysis * c. Conduct a t-test to compare means between two groups * d. Calculate confidence intervals * e. Conduct a Chi-square test
3. *Create a Data Table a. Import a sample dataset (e.g., sales data) into Excel. b. converts the dataset into an Excel Table using the “Format as Table” feature and apply appropriate styles. c. Create a dashboard sheet that summarizes key metrics (e.g., total sales, average sales per region) using tables. *Data Cleaning a. Identify and remove duplicates from a dataset. b. Use functions like TRIM, UPPER, LOWER, and PROPER to clean text data. c. Find and replace values using the Find & Replace feature.
4. Create a Pivot Table a. A basic pivot table from a dataset b. Specify and filter data in a pivot table c. Add a calculated field to a pivot table d. Group data within a pivot table. Refresh pivot table data after making changes to the source data. Filter and sort a PivotTable a. Apply a Filter to the PivotTable b. Sort Data in the Pivot Table. c. Add slicers to the PivotTable for interactive filtering.
5. Create a Pivot Chart a. A basic pivot chart from a dataset b. A dynamic pivot chart that updates based on user selection c. Group date items in a pivot table to summarize data by month or year d. Group product categories in a pivot table
6. *Create a Simple Chart a. A simple bar chart to visualize data sets b. A chart using non-adjacent cells to visualize data from different ranges. *Create a Chart Using the Chart Wizard a Select the chart you created and experiment with the Chart Tools options b. Modifying Charts c. Moving an Embedded Chart d. Sizing an Embedded Chart
7. *Change the Chart Type a. Create a basic bar chart using a dataset and change its type to a different chart b. Experiment with different data display options, such as adding data labels, changing the axis format, and adjusting the gridlines c. Experiment with position and style of the legend
8. a. Create a pie chart from a dataset b. Move the pie chart to a new worksheet for better visibility c. Emphasize a specific category by exploding a slice of the pie chart d. Customize the appearance of the pie chart for better presentation
9. * Create different types of plots.Write a Python script to save the plot in different formats: PNG, PDF, and SVG.
10. Application of data analytics across various industries through case study

Laboratory Equipment

1. Microsoft Office ,Office 365 1,2,3,4,5,6,7,8,9
2. Software: Editor: Python setup 10,11
3. Computer (i5 preferable), RAM minimum 8 GB onwards. All
4. Operating system: Windows 10 onward All

Learning Materials

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
.

Learning Websites & Portals

1. https://spreadsheetpoint.com/excel/dashboard-in-excel/ Advance Excel
2. https://www.javatpoint.com/how-to-create-a-dashboard-in-exce l Excel Dashboard
3. https://www.simplilearn.com/tutorials/excel-tutorial/data-an alysis-excel Data Visualization
4. https://www.freecodecamp.org/news/introduction-to-data-vizua lization-using-matplotlib/ Matplotlib in Python
5. https://archive.nptel.ac.in/courses/106/107/106107220/ Introduction to data analytics

For detail Syllabus of all other subjects of Information Technology, K scheme do visit Information Technology 5th Sem Syllabus for K scheme.

For all Information Technology results, visit MSBTE Information Technology all semester results direct links.