CBSE Class 12 Informatics Practices Syllabus 2022-23

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CBSE Class 12 Informatics Practices Syllabus 2022-23 includes Data Handling using Pandas and Data Visualization, Database Query using SQL, Introduction to Computer Networks, Societal Impacts etc for the session 2022 – 2023. Here is the detailed syllabus. To download class 12 Informatics Practices CBSE latest sample question papers for the 2023 exams, please install the myCBSEguide App which is the best mobile app for CBSE students. The myCBSEguide app not only provides you the CBSE class 12 Informatics Practices model question papers but it also provides class 12 Informatics Practices chapter-wise test papers, class 12 Informatics Practices best revision notes and other study material for class 12 Informatics Practices students.

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CBSE Class – 12
Informatics Practices (Code No. 065)
Syllabus (2022-23)

  1. Prerequisite: Informatics Practices – Class XI
  2. Learning Outcomes
    At the end of this course, students will be able to:

    • Create Series, Data frames and apply various operations.
    • Visualize data using relevant graphs.
    • Design SQL queries using aggregate functions.
    • Import/Export data between SQL database and Pandas.
    • Learn terminology related to networking and internet.
    • Identify internet security issues and configure browser settings.
    • Understand the impact of technology on society including gender and disability issues.
  3. Distribution of Marks and Periods

    Unit. No.Unit NameMarksPeriods TheoryPeriods PracticalTotal Period
    1Data Handling using Pandas and Data Visualization25252550
    2Database Query using SQL25201737
    3Introduction to Computer Networks1012012
    4Societal Impacts101414
  4. Unit Wise syllabus

    Unit 1: Data Handling using Pandas -I

    Introduction to Python libraries- Pandas, Matplotlib.
    Data structures in Pandas – Series and Data Frames.
    Series: Creation of Series from – ndarray, dictionary, scalar value; mathematical operations; Head and Tail functions; Selection, Indexing and Slicing.
    Data Frames: creation – from dictionary of Series, list of dictionaries, Text/CSV files; display; iteration; Operations on rows and columns: add, select, delete, rename; Head and Tail functions; Indexing using Labels, Boolean Indexing; Importing/Exporting Data between CSV files and Data Frames.
    Data Visualization
    Purpose of plotting; drawing and saving following types of plots using Matplotlib – line plot, bar graph, histogram
    Customizing plots: adding label, title, and legend in plots.

    Unit 2: Database Query using SQL

    Math functions: POWER (), ROUND (), MOD ().
    Text functions: UCASE ()/UPPER (), LCASE ()/LOWER (), MID ()/SUBSTRING ()/SUBSTR (), LENGTH (), LEFT (), RIGHT (), INSTR (), LTRIM (), RTRIM (), TRIM ().
    Date Functions: NOW (), DATE (), MONTH (), MONTHNAME (), YEAR (), DAY (), DAYNAME ().
    Aggregate Functions: MAX (), MIN (), AVG (), SUM (), COUNT (); using COUNT (*).
    Querying and manipulating data using Group by, Having, Order by.

    Unit 3: Introduction to Computer Networks

    Introduction to networks, Types of network: LAN, MAN, WAN.
    Network Devices: modem, hub, switch, repeater, router, gateway
    Network Topologies: Star, Bus, Tree, Mesh.
    Introduction to Internet, URL, WWW, and its applications- Web, email, Chat, VoIP.
    Website: Introduction, difference between a website and webpage, static vs dynamic web page, web server and hosting of a website.
    Web Browsers: Introduction, commonly used browsers, browser settings, add-ons and plug-ins, cookies.

    Unit 4: Societal Impacts

    Digital footprint, net and communication etiquettes, data protection, intellectual property rights (IPR), plagiarism, licensing and copyright, free and open source software (FOSS), cybercrime and cyber laws, hacking, phishing, cyber bullying, overview of Indian IT Act.
    E-waste: hazards and management.
    Awareness about health concerns related to the usage of technology.

    Project Work

    The aim of the class project is to create tangible and useful IT applications. The learner may identify a real-world problem by exploring the environment. e.g. Students can visit shops/business places, communities or other organizations in their localities and enquire about functioning of the organization, and how data are generated, stored, and managed.
    The learner can take data stored in csv or database file and analyze using Python libraries and generate appropriate charts to visualize.
    If an organization is maintaining data offline, then the learner should create a database using MySQL and store the data in tables. Data can be imported in Pandas for analysis and visualization.
    Learners can use Python libraries of their choice to develop software for their school or any other social good.
    Learners should be sensitized to avoid plagiarism and violation of copyright issues while working on projects. Teachers should take necessary measures for this. Any resources (data, image etc.) used in the project must be suitably referenced.
    The project can be done individually or in groups of 2 to 3 students. The project should be started by students at least 6 months before the submission deadline.

    Practical Marks Distribution

    S. No.Unit NameMarks
    1Programs using Pandas and Matplotlib8
    2SQL Queries7
    3Practical file (minimum of 15 programs based on Pandas, 4 based on Matplotlib and 15 SQL queries must be included)5
    4Project Work (using concepts learned in class XI and XII)5
  5. Suggested Practical List

    5.1 Data Handling

    1. Create a panda’s series from a dictionary of values and a ndarray
    2. Given a Series, print all the elements that are above the 75th percentile.
    3. Create a Data Frame quarterly sales where each row contains the item category, item name, and expenditure. Group the rows by the category and print the total expenditure per category.
    4. Create a data frame for examination result and display row labels, column labels data types of each column and the dimensions
    5. Filter out rows based on different criteria such as duplicate rows.
    6. Importing and exporting data between pandas and CSV file

    5.2 Visualization

    1. Given the school result data, analyses the performance of the students on different parameters, e.g subject wise or class wise.
    2. For the Data frames created above, analyze, and plot appropriate charts with title and legend.
    3. Take data of your interest from an open source (e.g., aggregate and summarize it. Then plot it using different plotting functions of the Matplotlib library.

    5.3 Data Management

    1. Create a student table with the student id, name, and marks as attributes where the student id is the primary key.
    2. Insert the details of a new student in the above table.
    3. Delete the details of a student in the above table.
    4. Use the select command to get the details of the students with marks more than 80.
    5. Find the min, max, sum, and average of the marks in a student marks table.
    6. Find the total number of customers from each country in the table (customer ID, customer Name, country) using group by.
    7. Write a SQL query to order the (student ID, marks) table in descending order of the marks.

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