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JNTUA B.TECH R20 1-2 Syllabus For python programming & data science PDF 2022

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JNTUA B.TECH R20 1-2 Syllabus For python programming & data science PDF 2022

Get Complete Lecture Notes for python programming & data science on Cynohub APP

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You will be able to find information about python programming & data science along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding python programming & data science after reading this blog. python programming & data science has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. python programming & data science can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.

All of the Topic and subtopics related to python programming & data science are mentioned below in detail. If you are having a hard time understanding python programming & data science or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.

python programming & data science Unit One

Introduction to Python

Features of Python, Data types, Operators, Input and output, Control
Statements.
Strings: Creating strings and basic operations on strings, string testing methods. Lists, Dictionaries,
Tuples.

python programming & data science Unit Two

Functions

Defining a function, Calling a function, returning multiple values from a function,
functions are first class objects, formal and actual arguments, positional arguments, recursive
functions.
Exceptions: Errors in a Python program, exceptions, exception handling, types of exceptions, the
except block, the assert statement, user-defined exceptions.

Get Complete Lecture Notes for python programming & data science on Cynohub APP

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python programming & data science Unit Three

Introduction to NumPy, Pandas, Matplotlib

Exploratory Data Analysis (EDA), Data Science life cycle, Descriptive Statistics, Basic tools (plots,
graphs and summary statistics) of EDA, Philosophy of EDA. Data Visualization: Scatter plot, bar
chart, histogram, boxplot, heat maps, etc.

python programming & data science Unit Four

Introduction to Pattern Recognition and Machine Learning

Patterns, features, pattern representation,
the curse of dimensionality, dimensionality reduction. Classification—linear and non-linear. Bayesian,
Perceptron, Nearest neighbor classifier, Logistic regression, Naïve-Bayes, decision trees and random
forests; boosting and bagging.Clustering—partitional and hierarchical; k-means clustering.
Regression.
Cost functions, training and testing a classifier. Cross-validation, Class-imbalance – ways of handling,
Confusion matrix, evaluation metrics

python programming & data science Unit Five

Introduction to Deep Learning

Multilayer perceptron. Backpropagation. Loss functions.
Hyperparameter tuning, Overview of RNN, CNN and LSTM.
Overview of Data Science Models: Applications to text, images, videos, recommender systems, image
classification, Social network graphs

python programming & data science Course Objectives

To learn the fundamentals of Python.
 To discuss the concepts of Functions and Exceptions.
 To familiarize with Python libraries for Data Analysis and Data Visualization.
 To introduce preliminary concepts in Pattern Recognition and Machine learning.
 To provide an overview of Deep Learning and Data Science models.

python programming & data science Course Outcomes

N/A

python programming & data science Text Books

N/A

python programming & data science Reference Books

N/A

Scoring Marks in python programming & data science

Scoring a really good grade in python programming & data science is a difficult task indeed and CynoHub is here to help!. Please watch the video below and find out how to get 1st rank in your B.tech examinations . This video will also inform students on how to score high grades in python programming & data science. There are a lot of reasons for getting a bad score in your python programming & data science exam and this video will help you rectify your mistakes and help you improve your grades.

Information about JNTUA B.Tech R20 python programming & data science was provided in detail in this article. To know more about the syllabus of other Engineering Subjects of JNTUH check out the official CynoHub application. Click below to download the CynoHub application.

Get Complete Lecture Notes for python programming & data science on Cynohub APP

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