Food Technology • 3rd SemesterCore / Standard CurriculumChange Track

Food Technology — 3rd Semester Syllabus

Food Processing and Preservation

Browse 3rd Semester PYQs

Credits Allocation Table (L-T-P Structure)

Course TitleCodeLTPCredits
Engineering Mathematics -III (PDE, Prob/Stat)1153013014
Principles of Food Preservation1153023014
Food Processing Operations1153033003
Food Microbiology1153043003
Python Programming1153053003
Universal Human Values1153063003
Indian Knowledge System1153073000
Food Processing Operations Lab115303P0021
Food Microbiology Lab115304P0021
Python Programming Lab115305P0021
Internship-I115308---2
TOTAL----25

Engineering Mathematics-III (PDE, Prob/Stat)

115301
Theory Course • 6 Units
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Unit 1.0

  • Definition of partial differential equations
  • First order partial differential equations
  • Solutions of first order linear PDEs
  • Solution to homogenous and non-homogenous linear partial differential equations of second order by complimentary function and particular integral method

Unit 2.0

  • Second-order linear equations and their classification
  • Initial and boundary conditions
  • D'Alembert's solution of the wave equation
  • Duhamel's principle for one dimensional wave equation
  • Heat diffusion and vibration problems
  • Separation of variables method to simple problems in Cartesian coordinates
  • The Laplacian in plane
  • Cylindrical and spherical polar coordinates
  • Solutions with Bessel functions and Legendre functions
  • One dimensional diffusion equation and its solution by separation of variables

Unit 3.0

  • Probability spaces
  • Conditional probability
  • Independence
  • Discrete random variables
  • Independent random variables
  • The multinomial distribution
  • Poisson approximation to the binomial distribution
  • Infinite sequences of Bernoulli trials
  • Sums of independent random variables
  • Expectation of discrete random variables
  • Moments
  • Variance of a sum
  • Correlation coefficient
  • Chebyshev's inequality

Unit 4.0

  • Continuous random variables and their properties
  • Distribution functions and densities
  • Normal
  • Exponential and gamma densities
  • Bivariate distributions and their properties
  • Distribution of sums and quotients
  • Conditional densities
  • Bayes' rule

Unit 5.0

  • Basic statistics
  • Measures of central tendency: moments
  • Skewness and kurtosis
  • Probability distributions: binomial
  • Poisson and normal - evaluation of statistical parameters for these three distributions
  • Correlation and regression - rank correlation
  • Curve fitting by the method of least squares fitting of straight lines
  • Second degree parabolas and more general curves

Unit 6.0

  • Test of significance: large sample test for single proportion
  • Difference of proportions
  • Tests for single mean
  • Difference of means
  • And difference of standard deviations
  • Test for ratio of variances - chi- square test for goodness of fit and independence of attributes

Principles of Food Preservation

115302
Theory Course • 6 Units
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Unit 1.0: Food Spoilage and Food Preservation

  • Parameters of foods that affect their stability
  • Causes of food spoilage
  • Microorganisms and food spoilage
  • Enzymatic reactions and chemical changes in foods
  • Food preservation principles
  • Methods

Unit 2.0: Thermal Processing of Food

  • Thermal destruction of microbial cells and bacteria spores
  • Kinetics of microbial death
  • Heat penetration into foods
  • Method of determining lethality of thermal processes
  • Thermal destruction of enzymes
  • Mechanisms of heat transfer in food
  • Blanching
  • Pasteurization
  • And sterilization
  • Thermal processing of foods in containers and outside containers
  • Principle of aseptic technology
  • Thermal destruction of nutrients and quality factors
  • Optimization of the thermal processes fornutrient retention
  • Thermal processing equipment and technology

Unit 3.0: Chilling of Food

  • Chilling of food: normal behaviour of foods stored at chilling temperatures: animal tissues
  • Plant tissues and non-tissue food
  • Quality loss in foods stored at chilling temperatures
  • Temperature
  • Relative humidity and other conditions selected for chilling storage
  • Storage of food in chilled atmospheres of modified composition
  • Chilling equipment

Unit 4.0: Freezing of Food

  • Freezing of foods: effect of low temperature on microbial activity
  • Enzymatic activity and rate of chemical changes
  • Crystallization of water: nucleation
  • Crystal growth
  • Physical and chemical changes associated with ice formation
  • Prefreezing treatments for major classes of natural food tissues
  • Freezing methods and equipment
  • Storage of frozen foods

Unit 5.0: Dehydration and Concentration of Food

  • Water activity and food preservation: free and bound water in foods
  • Water activity and sorption behaviour of foods
  • Water activity and microbial spoilage
  • Water activity and enzymatic reactions
  • Effects of water activity on the chemical deterioration of foods
  • Dehydration of foods: mass and heat balance in air drying
  • Constant and falling rate period drying
  • Psychometric chart
  • Analysis of drying under constant external conditions
  • Shrinkage during drying
  • Nutrient destruction and other deteriorative reactions occurring during drying
  • Industrial drying processes and equipment for foods
  • Freeze drying
  • Reconstitutability of dried foods

Unit 6.0: Other Methods of Food Processing

  • Recent developments in food processing: extrusion
  • Food packaging
  • Food irradiation
  • High pressure processing
  • Ultrasound technology
  • Etc.

Food Processing Operations

115303
Theory Course • 6 Units
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Unit 1.0: Unit Operations -Size Reduction

  • Size reduction: theory of communition
  • Ritinger's law
  • Kick's law
  • Bond's law and their applications in calculation of energy required in grinding
  • Crushing efficiency
  • Size reduction equipment used in food industry

Unit 2.0: Mixing

  • Mixing: solid mixing
  • Mixing index
  • Rate of mixing
  • Theory of liquid mixing
  • Equipment for liquid and solid mixing

Unit 3.0: Sieving and Sedimentation

  • Separation based on size
  • Effectiveness of screens
  • Types of screens
  • Factors affecting the sieving process
  • Fineness modules and particle size distribution
  • Gravitational sedimentation of particles in liquids and gases
  • Sedimentation equipment

Unit 4.0: Centrifugal separation

  • Basic equation
  • Centrifugal clarification
  • Equipment
  • Filtration: fundamental equation for filtration
  • Filtration equipment
  • Crystallization: rate of crystallization
  • Crystallization equilibrium

Unit 5.0: Distillation

  • Liquid vapor equilibrium
  • Distillation of binary mixtures
  • Simple distillation
  • Continuous distillation
  • Flash distillation
  • Steam distillation

Unit 6.0: Leaching and extraction

  • Gas - liquid equilibria
  • Solid - liquid equilibria
  • Extraction-solid liquid extraction
  • Liquid- liquid extraction
  • Stage equilibrium extraction

Food Microbiology

115304
Theory Course • 6 Units
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Unit 1.0: Food Microbiology

  • Developments in food microbiology
  • Prokaryotic and eukaryotic cell
  • Morphology
  • Structure
  • Microbiology and reproduction of bacteria
  • Yeast and mould

Unit 2.0: Culture and Microbial Growth

  • Serial dilution
  • Pour plate
  • Streak plate
  • Spread plate
  • Slant broth and enrichment culture
  • Lyophilization
  • Growth curves
  • Synchronous growth
  • Doubling/generation time
  • Intrinsic and extrinsic factors
  • Relationship between number of generations and total number of microbes

Unit 3.0: Food Spoilage

  • Microbiology of raw milk and fermented milk products viz. yoghurt
  • Cheese
  • Cereals products
  • Fruits and vegetable
  • Meat and meat products
  • Egg and fish

Unit 4.0: Spoilage and their effect on Human I

  • Bacterial and fungal food spoilage
  • Food poisoning
  • Food borne infection
  • Food borne intoxication

Unit 5.0: Spoilage and their effect on Human II

  • Toxins produced by Staphylococcus
  • Clostridium
  • Aspergillum
  • Bacterial pathogens- Salmonella
  • Bacillus
  • Listeria
  • E. coli
  • Shigella
  • Campylobacter

Unit 6.0: Microbial Control

  • Source of microorganisms
  • Physical and chemical agents used in microbial control
  • Disinfected agents and its dynamics

Python Programming

115305
Theory Course • 6 Units
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Unit 1.0: Basics Programming Syntax, Conditional and Iterative Statements

  • Procedure oriented vs. object-oriented approach of programming
  • Python character set
  • Python tokens
  • Variables
  • Concept of lvalue and rvalue
  • Use of comments
  • Data types: number (integer, floating point, complex)
  • Boolean
  • Sequence (string, list, tuple)
  • None
  • Mapping
  • (dictionary)
  • Mutable and immutable data types
  • Operators: arithmetic operators
  • Relational operators
  • Logical operators
  • Assignment operator
  • Augmented assignment operators
  • Expressions
  • Statement
  • Type conversion & input/output: precedence of operators
  • Expression
  • Evaluation of expression
  • Conditional statements: simple if statement
  • If- else statement
  • If- elif-else statement
  • Iterative statements: while loop
  • For loop
  • Range function
  • Break and continue statements
  • Nested loops

Unit 2.0: String, List, Tuples, Set and Dictionary

  • String: indexing
  • String operations (concatenation, repetition, membership & slicing)
  • Traversing a string using loops
  • Built-in functions
  • Lists: introduction
  • Indexing
  • List operations: concatenation
  • Repetition
  • Membership & slicing
  • Traversing a list
  • Built- in list functions
  • Linear search on list of numbers and counting the frequency of elements in a list
  • Tuples: creating
  • Initializing
  • Accessing elements
  • Tuple assignment
  • Performing operations on tuples
  • Tuple methods and built-in functions
  • Nested tuples
  • Set: creating set
  • Traversing
  • Adding
  • Removing data in set
  • Performing set operations like join
  • Union intersection
  • Difference
  • Dictionary: accessing items in a dictionary using keys
  • Mutability of dictionary: adding a new item
  • Modifying an existing item
  • Built-in dictionary functions

Unit 3.0: Python Functions, Modules and Packages

  • Functions: types of function (built- in functions, functions defined in module, user defined functions)
  • Creating user defined function
  • Arguments and parameters
  • Default parameters
  • Positional parameters
  • Lambda functions
  • Returning value
  • Scope of a variable: global scope
  • Local scope
  • Modules and packages: importing module using 'import' regular expressions
  • Exception handling
  • PyPI python package index
  • Pip python package manager
  • Importing libraries and functions

Unit 4.0: Object-Oriented Programming (OOP)

  • OOPs object oriented programming concepts and approach
  • Abstraction
  • Encapsulation
  • Class
  • Object
  • Class method vs static method in python
  • Class and static variable
  • Constructor and destructors in python
  • Inheritance: types of inheritance: single
  • Multiple
  • Multilevel
  • Hierarchical
  • Polymorphism: polymorphism with class method
  • Polymorphism with inheritance
  • Method overriding
  • Overloading

Unit 5.0: Exception and File Handling in Python

  • Exception handling: syntax errors
  • Exceptions
  • Need of exception handling
  • User-defined exceptions
  • Raising exceptions
  • Handling exceptions
  • Catching exceptions
  • Try except - else clause
  • Try - finally clause
  • Recovering and continuing with finally
  • Built-in exception classes
  • File handling: text file and binary file
  • File types
  • Open and close files
  • Reading and writing text files
  • Reading and writing binary files
  • File access modes

Unit 6.0: Data Analysis with Pandas

  • Pandas data structures: series
  • Declaration
  • Selecting elements
  • Assigning values
  • Filtering values
  • Operations
  • Mathematical functions
  • Evaluating values
  • Handling missing data
  • Creating series from dictionaries
  • Adding two series
  • Data frame: defining
  • Selecting elements
  • Assigning values
  • Membership
  • Deleting a column
  • Filtering
  • Index objects: indexing
  • Re-indexing
  • Dropping
  • Sorting and ranking
  • Descriptive statistics data loading: reading and writing csv
  • Xls
  • Text data files
  • Data cleaning and preparation: handling missing data
  • Removing duplicates
  • Replacing values
  • Vectorized string methods
  • Hierarchical indexing
  • Merging and combining
  • Data aggregation and grouping

Universal Human Values

115306
Theory Course • 6 Units
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Unit 1.0: Introduction to Value Education

  • Right understanding
  • Relationship and physical facility (holistic development and the role of education)
  • Understanding value education sharing about oneself
  • Self-exploration as the process for value education
  • Continuous happiness and prosperity the basic human aspirations
  • Exploring human consciousness
  • Happiness and prosperity - current scenario
  • Method to fulfill the basic human aspirations

Unit 2.0: Harmony in the Human Being

  • Understanding human being as the co-existence of the self and the body
  • Distinguishing between the needs of the self and the body
  • The body as an instrument of the self
  • Understanding harmony in the self
  • Harmony of the self with the body
  • Programme to ensure self-regulation and health

Unit 3.0: Harmony in the Family and Society

  • Harmony in the family the basic unit of human interaction
  • 'Trust' the foundational value in relationship
  • 'Respect' as the right evaluation
  • Other feelings
  • Justice in human- to-human relationship
  • Understanding harmony in the society
  • Vision for the universal human order

Unit 4.0: Harmony in the Nature/Existence

  • Understanding harmony in the nature
  • Interconnectedness
  • Self-regulation and mutual fulfilment among the four orders of nature
  • Realizing existence as co-existence at all levels
  • The holistic perception of harmony in existence

Unit 5.0: Implications of the Holistic Understanding - a Look at Professional

  • Natural acceptance of human values
  • Definitiveness of (ethical) human conduct
  • A basis for humanistic education
  • Humanistic constitution and universal human order
  • Competence in professional ethics
  • Holistic technologies
  • Production systems and management models-typical case studies
  • Strategies for transition towards value-based life and profession

Unit 6.0: Competence in Professional Ethics

  • Competence in professional ethics
  • Holistic technologies
  • Production systems and management models-typical case studies
  • Strategies for transition towards value-based life and profession

Indian Knowledge System

115307
Theory Course • 6 Units
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Unit 1.0: Introduction to Indian Knowledge Systems

  • Overview of IKS
  • Organization of IKS
  • Conception and constitution of knowledge in indian tradition
  • The oral tradition
  • Models and strategies of IKS

Unit 2.0: Overview of IKS Domains

  • The vedasas the basis of IKS
  • Overview of all the six vedängas

Unit 3.0: Relevance in Current Technical Education System I

  • Relevance of following IKS domains in present technical education system: arthashastra (indian economics and political systems)
  • Ganitaand jyamiti(indianmathematics
  • Astronomy and geometry
  • Rasayana (indianchemical sciences)

Unit 4.0: Relevance in Current Technical Education System II

  • Ayurveda (indian biological sciences / diet & nutrition)
  • Jyotishvidya (observational astronomy and calendar systems)
  • Prakriti vidya(indian system of terrestrial/ material sciences/ecology and atmospheric sciences)

Unit 5.0: Relevance in Current Technical Education System III

  • Vastu vidya(indian system of aesthetics-iconography and built-environment /architecture)
  • Nyayashastra(indian systems of social ethics
  • Logic and law)

Unit 6.0: Advanced IKS Domains

  • Shilpa andnatyashastra (indian classical arts: performing and fine arts)
  • Sankhyaand yoga darshna(indian psychology
  • Yoga and consciousness studies)
  • Vrikshayurveda(plant science/sustainable agriculture/food preservation methods)

Food Processing Operations Lab

115303P
Laboratory Subject • 1 Units
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Topics Part 1

  • D.F.Z value for a heating process meant for inactivation of microorganisms.
  • Thermal process time by formula method
  • Thermal process time by graphical method
  • Steam properties using Mollier diagram
  • Steam properties using steam tables
  • Boiling point elevation
  • Multiple effect evaporator
  • Relative humidity and other thermodynamic properties of air using Psychrometric chart
  • Drying characteristics of a food material during convective dehydration
  • Moisture diffusivity of a food material during dehydration.
  • Activation energy for dehydration of a food sample.
  • Freeze drying time determined by experiment and from modified Plank's equation
  • Freezing point depression of a food material.
  • Freezing curve for pure water and a food material.
  • Freezing time for a given food sample using Heislier charts or unsteady state heat transfer solutions.

Prescribed Experiments

  1. D.F.Z value for a heating process meant for inactivation of microorganisms.
  2. Thermal process time by formula method
  3. Thermal process time by graphical method
  4. Steam properties using Mollier diagram
  5. Steam properties using steam tables
  6. Boiling point elevation
  7. Multiple effect evaporator
  8. Relative humidity and other thermodynamic properties of air using Psychrometric chart
  9. Drying characteristics of a food material during convective dehydration
  10. Moisture diffusivity of a food material during dehydration.
  11. Activation energy for dehydration of a food sample.
  12. Freeze drying time determined by experiment and from modified Plank's equation
  13. Freezing point depression of a food material.
  14. Freezing curve for pure water and a food material.
  15. Freezing time for a given food sample using Heislier charts or unsteady state heat transfer solutions.

Food Microbiology Lab

115304P
Laboratory Subject • 1 Units
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Topics Part 1

  • Carbohydrates in the given food sample
  • Browning reaction and inhibition of browning reaction.
  • Acid value, RM value and Polenske value of given oil or fat sample
  • Amount of fat in the given food samples
  • Protein by Kjeldhal, electrophoresis methods
  • Pectic substances and pectin in fruit
  • Vitamins in foods
  • Gram staining technique of bacteria
  • Size of a given microbial cell
  • Total viable count in a culture
  • Growth curve of microorganisms.
  • Pure culture using different techniques.
  • Analysis of food sample by standard plate count (SPC) method.
  • Quality of milk by methylene blue reduction (MBRT) tes
  • Presumptive test for coliforms in milk.

Prescribed Experiments

  1. Carbohydrates in the given food sample
  2. Browning reaction and inhibition of browning reaction.
  3. Acid value, RM value and Polenske value of given oil or fat sample
  4. Amount of fat in the given food samples
  5. Protein by Kjeldhal, electrophoresis methods
  6. Pectic substances and pectin in fruit
  7. Vitamins in foods
  8. Gram staining technique of bacteria
  9. Size of a given microbial cell
  10. Total viable count in a culture
  11. Growth curve of microorganisms.
  12. Pure culture using different techniques.
  13. Analysis of food sample by standard plate count (SPC) method.
  14. Quality of milk by methylene blue reduction (MBRT) tes
  15. Presumptive test for coliforms in milk.

Python Programming Lab

115305P
Laboratory Subject • 1 Units
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Topics Part 1

  • a) Download and Install IDLE. Write and execute Python program to- b) Calculate the Area of a Triangle where its three sides a, b, c are given. $s=(a+b+c)/2$ Area=square root of $s(s-a)(s-b)(s-c)$ (write program without using function) c) Swap Two Variables d) Solve quadratic equation for real numbers.
  • Write and execute Python program to- a) Check if a Number is Positive, Negative or zero. b) Check whether the given year is a Leap Year. c) Print all Prime Numbers in an Interval. d) Display the multiplication Table based on the given input. e) Print the Fibonacci sequence. f) Find the Factorial of a Number.
  • Write and execute Python program to- a) Check whether the string is Palindrome b) Reverse words in a given String in Python c) identify in a strings the name, position and counting of vowels. d) Count the Number of matching characters in a pair of string (set) e) Python program for removing i-th character from a string
  • Write and execute Python program to- a) find largest number in a given list without using max(). b) find the common numbers from two lists. c) create a list of even numbers and another list of odd numbers from a given list. d) To find number of occurrences of given number without using built-in methods.
  • Write and execute Python program to- a) find the index of an item of a tuple. b) find the length of a tuple. c) to reverse a tuple. d) Write a Python program to sort a list of tuple by its float element. Sample data: [('item1', '12.20'), ('item2', '15.10'), ('item3', '24.5')] Expected Output: [('item3', '24.5'), ('item2', '15.10'), ('item1', '12.20')]
  • Write and execute Python program to- a) create an intersection of sets. b) create a union of sets. c) create set difference. d) check if two given sets have no elements in common.
  • Write and execute Python program to- a) Write a Python script to concatenate two dictionaries to create a new one b) Write a Python script to merge two Python dictionaries. c) Write a Python program to combine two dictionary adding values for common keys. d1= {'a': 100, 'b': 200, 'c':300} d2= {'a': 300, 'b': 200, 'd': 400} Sample output: d({'a': 400, 'b': 400, 'd': 400, 'c': 300})
  • Write and execute Python program to- a) Write a Python function for reversing a string and call it. b) Write a Python function for calculating compound interest and call it. c) Write a Python function for calculating the factorial of a number and call it to calculate $!n/(!r)*!(n-r)$ where symbol "!" stands for factorial.
  • Write program using OOP approach to a) create an instance of a specified class and display the namespace of the said instance b) create a Python class named Student with two attributes: student_id, student_name. Add a new attribute: student class. Create a function to display all attributes and their values in the Student class. c) Create a Python class named Student with two instances student1, student2 and assign values to the instances' attributes. Print all the attributes of the student1, student2 instances d) Write programs to demonstrate use of following types of inheritance: i. Single inheritance ii. Multiple inheritance iii. Multilevel inheritance e) Demonstrate use of polymorphism with following situations: i. Polymorphism in operator ii. Polymorphism in user defined method iii. Polymorphism in built-in function iv. Polymorphism with class method v. Polymorphism with method overriding
  • Using exception handling feature such as try...except, try finally- write minimum three programs to handle following types of exceptions. a) i. TypeError ii. NameError iii. Index Error iv. KeyError v. ValueError vi. IOError vii. ZeroDivisionError b) Write Python program to demonstrate file operations.
  • Working with a Series using Pandas a) Create a series using list and dictionary. 10b. Create a series using NumPy functions inPandas. b) Print the index and values of series. c) Print the first and last few rows from theseries.
  • Working with Data Frame Rows a) Slicing Data Frame using loc and iloc. 11b. Filter multiple rows using isin. b) Select first n rows and last n rows c) Select rows randomly n rows and fractions of rows (use df. sample method) d) Count the number of rows with eachunique value of variables e) Select nlargest and nsmallest values. 11g. Order/sort the rows
  • Merge and combine data a) Perform the append, concat and combinefirst operations on Data Frames. b) Apply different types of merge on data. 12c. Use a query method to filter Data Frame c) with multiple conditions.

Prescribed Experiments

  1. a) Download and Install IDLE. Write and execute Python program to- b) Calculate the Area of a Triangle where its three sides a, b, c are given. $s=(a+b+c)/2$ Area=square root of $s(s-a)(s-b)(s-c)$ (write program without using function) c) Swap Two Variables d) Solve quadratic equation for real numbers.
  2. Write and execute Python program to- a) Check if a Number is Positive, Negative or zero. b) Check whether the given year is a Leap Year. c) Print all Prime Numbers in an Interval. d) Display the multiplication Table based on the given input. e) Print the Fibonacci sequence. f) Find the Factorial of a Number.
  3. Write and execute Python program to- a) Check whether the string is Palindrome b) Reverse words in a given String in Python c) identify in a strings the name, position and counting of vowels. d) Count the Number of matching characters in a pair of string (set) e) Python program for removing i-th character from a string
  4. Write and execute Python program to- a) find largest number in a given list without using max(). b) find the common numbers from two lists. c) create a list of even numbers and another list of odd numbers from a given list. d) To find number of occurrences of given number without using built-in methods.
  5. Write and execute Python program to- a) find the index of an item of a tuple. b) find the length of a tuple. c) to reverse a tuple. d) Write a Python program to sort a list of tuple by its float element. Sample data: [('item1', '12.20'), ('item2', '15.10'), ('item3', '24.5')] Expected Output: [('item3', '24.5'), ('item2', '15.10'), ('item1', '12.20')]
  6. Write and execute Python program to- a) create an intersection of sets. b) create a union of sets. c) create set difference. d) check if two given sets have no elements in common.
  7. Write and execute Python program to- a) Write a Python script to concatenate two dictionaries to create a new one b) Write a Python script to merge two Python dictionaries. c) Write a Python program to combine two dictionary adding values for common keys. d1= {'a': 100, 'b': 200, 'c':300} d2= {'a': 300, 'b': 200, 'd': 400} Sample output: d({'a': 400, 'b': 400, 'd': 400, 'c': 300})
  8. Write and execute Python program to- a) Write a Python function for reversing a string and call it. b) Write a Python function for calculating compound interest and call it. c) Write a Python function for calculating the factorial of a number and call it to calculate $!n/(!r)*!(n-r)$ where symbol "!" stands for factorial.
  9. Write program using OOP approach to a) create an instance of a specified class and display the namespace of the said instance b) create a Python class named Student with two attributes: student_id, student_name. Add a new attribute: student class. Create a function to display all attributes and their values in the Student class. c) Create a Python class named Student with two instances student1, student2 and assign values to the instances' attributes. Print all the attributes of the student1, student2 instances d) Write programs to demonstrate use of following types of inheritance: i. Single inheritance ii. Multiple inheritance iii. Multilevel inheritance e) Demonstrate use of polymorphism with following situations: i. Polymorphism in operator ii. Polymorphism in user defined method iii. Polymorphism in built-in function iv. Polymorphism with class method v. Polymorphism with method overriding
  10. Using exception handling feature such as try...except, try finally- write minimum three programs to handle following types of exceptions. a) i. TypeError ii. NameError iii. Index Error iv. KeyError v. ValueError vi. IOError vii. ZeroDivisionError b) Write Python program to demonstrate file operations.
  11. Working with a Series using Pandas a) Create a series using list and dictionary. 10b. Create a series using NumPy functions inPandas. b) Print the index and values of series. c) Print the first and last few rows from theseries.
  12. Working with Data Frame Rows a) Slicing Data Frame using loc and iloc. 11b. Filter multiple rows using isin. b) Select first n rows and last n rows c) Select rows randomly n rows and fractions of rows (use df. sample method) d) Count the number of rows with eachunique value of variables e) Select nlargest and nsmallest values. 11g. Order/sort the rows
  13. Merge and combine data a) Perform the append, concat and combinefirst operations on Data Frames. b) Apply different types of merge on data. 12c. Use a query method to filter Data Frame c) with multiple conditions.

Internship - I

115308
Laboratory Subject • Course Details
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