JNTUA B.TECH R 19 3-2 Syllabus For Data science PDF 2022
February 12, 2022 2022-02-12 20:22JNTUA B.TECH R 19 3-2 Syllabus For Data science PDF 2022
JNTUA B.TECH R 19 3-2 Syllabus For Data science PDF 2022
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You will be able to find information about 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 Data science after reading this blog. Data science has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. 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 Data science are mentioned below in detail. If you are having a hard time understanding 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.
Data science Unit One
Introduction to Data Science, A Crash Course in Python, Visualising Data
Data science Unit Two
Linear Algebra, Statistics, Probability, Hypothesis and Inference, Gradient Descent.
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Data science Unit Three
Getting Data, Working with Data, Machine Leaning, k-Nearest Neighbors, Naïve Bayes.
Data science Unit Four
Simple Linear Regression, Multiple Regression, Logistic Regression, Decision Trees, Neural Networks.
Data science Unit Five
Clustering, Natural Language Processing, Network Analysis, Recommender Systems.Database and SQL, MapReduce
Data science Course Objectives
This course is designed to:Understand the approaches for handling data related problemsExplore the mathematical concepts required for Data scienceExplain the basic concepts of data science.Elucidate various Machine Learning algorithms.Introduce Natural Language Processing and Recommender Systems
Data science Course Outcomes
After completion of this course the student would be able toVisualize the data using bar charts, line charts and scatter plots(L4). Analyse Correlation between two data objects (L4). Demonstrate feature selection and dimensionality reduction.(L2)Solve decision making problems using k-NN, Naïve Bayes, SVM and Decision.Trees (L3).Determine Clusters in data using k-means and Hierarchical Clustering methods (L3).Designbasic SQL Operations using NotQuiteABase(L6)Demonstrate the way to use machine learning algorithms using python. (L2)
Data science Text Books
1.Data Science from Scratch, First Principles with Python -Joel Grus, O’Reilly, First Edition
Data science Reference Books
1.The Data Science Handbook, Field Cady, WILEY.
2.An Introduction to Data Science, Jeffrey M. Stanton, Jeffrey Stanton, 2012
Scoring Marks in Data science
Scoring a really good grade in 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 Data science. There are a lot of reasons for getting a bad score in your Data science exam and this video will help you rectify your mistakes and help you improve your grades.
Information about JNTUA B.Tech R 19 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 Data science on Cynohub APP
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