Course Modules

Introduction to the Course

Introduction to the Course Introduction to the Course

Page

Ted Talk on Data Science Ted Talk on Data Science 1

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Page

Trends In Python Trends In Python 2

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Page

Course Template Course Template 3

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Page

Evaluation Scheme Evaluation Scheme 4

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Page

Experiential Learning Experiential Learning 5

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Unit 1: Basics of Python Programming

Unit 1: Basics of Python Programming Unit 1: Basics of Python Programming

Context Module Sub Header

Week 1 1

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Context Module Sub Header

L01_Evaluation Scheme and Rubrics 2

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Context Module Sub Header

L02_Introduction To Python 3

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External Url

L02_Anconda Installation and Jupyter Notebook Set-up L02_Anconda Installation and Jupyter Notebook Set-up 4

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Attachment

L02_Python_Introduction_History.pptx L02_Python_Introduction_History.pptx 5

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Attachment

L02_Basics of Python.pptx L02_Basics of Python.pptx 6

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Context Module Sub Header

P01_Installation of Python IDE Anconda and Set-up Jupyter Notebook 7

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Context Module Sub Header

P02_Explore the Jupyter Notebook and Spyder with basics commands of python 8

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Attachment

Notebook_on_Introduction.ipynb Notebook_on_Introduction.ipynb 9

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Context Module Sub Header

Week 2: Basic Operations and Data Types 10

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Attachment

L03_Basic Math.pptx L03_Basic Math.pptx 11

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Attachment

L03_Variables.pptx L03_Variables.pptx 12

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Attachment

L03_Types of Data.pptx L03_Types of Data.pptx 13

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L04_Control Structures and Decision 14

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L04_Decisions.pptx L04_Decisions.pptx 15

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Context Module Sub Header

P03_Expressions_Variables_Datatypes_in_Python. 17

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Attachment

01_Notebook_Data and Expressions.ipynb 01_Notebook_Data and Expressions.ipynb 18

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Attachment

01_Drill_Variables.ipynb 01_Drill_Variables.ipynb 19

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Attachment

02_Drill_Variables.ipynb 02_Drill_Variables.ipynb 20

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Context Module Sub Header

P04_program to print each letter of a word. Repeat this process for atleast five words 21

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Context Module Sub Header

Week 3 22

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Context Module Sub Header

L05_Loops in Python 23

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L05_Loops.pptx L05_Loops.pptx 24

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L05_Comments.pptx L05_Comments.pptx 25

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L05_Input_output.pptx L05_Input_output.pptx 26

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Context Module Sub Header

P05_Study of Python commands for List 27

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Context Module Sub Header

P06_commands to find length of the list and check if a fruit exists in the list, create copy of the list. 28

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Unit 2: Collections and Functions

Unit 2: Collections and Functions Unit 2: Collections and Functions

Attachment

L06_List in Python.pptx L06_List in Python.pptx 2

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L06_Self_test_lists.ipynb L06_Self_test_lists.ipynb 3

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L07_More_About_Lists.ipynb L07_More_About_Lists.ipynb 4

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Attachment

Pract_Drill_Lists.ipynb Pract_Drill_Lists.ipynb 7

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Pract_Drill_Lists.ipynb Pract_Drill_Lists.ipynb 8

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Context Module Sub Header

Week 4: Dictionary and Array in Python 9

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L08_Dictionaries in Python.pptx L08_Dictionaries in Python.pptx 10

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L08_Dictionary and Sets Jupyter Notebook.ipynb L08_Dictionary and Sets Jupyter Notebook.ipynb 11

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Tuple in Python.pptx Tuple in Python.pptx 12

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Lect10_Functions in Python.pptx Lect10_Functions in Python.pptx 16

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L09_Numpy in Python.pptx L09_Numpy in Python.pptx 23

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01_Notebook_slicing_list_array.ipynb 01_Notebook_slicing_list_array.ipynb 24

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Context Module Sub Header

P09_Give commands to create a dictionary of brand, model and year, access a specific item, change value of any one item 25

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Context Module Sub Header

P10_Check prime and Armstrong number by making functions. 26

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Let11_Call By Value and Call By reference in Python.pptx Let11_Call By Value and Call By reference in Python.pptx 28

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L12_Recursion In Python.pptx L12_Recursion In Python.pptx 29

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Quiz

Quiz 2: Collections In Python Quiz 2: Collections In Python 10 33

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Unit 3: Object Oriented Concepts for Python

Unit 3: Object Oriented Concepts for Python Unit 3: Object Oriented Concepts for Python

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Week 7: Class and Objects 1

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L13_Introduction to Object Oriented Programming.pptx L13_Introduction to Object Oriented Programming.pptx 2

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L14_Encapsulation in Python.pptx L14_Encapsulation in Python.pptx 3

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Extra_Materail_OOPs.pptx Extra_Materail_OOPs.pptx 4

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01_Drill_Classes and Objects.ipynb 01_Drill_Classes and Objects.ipynb 5

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P13_Create a class “Person” with atleast five attributes. Create five objects and display. 6

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Context Module Sub Header

P14_Write a program to show the OOPS concepts: Encapsulation 7

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01_Drill_Classes and Objects-SOLUTION.ipynb 01_Drill_Classes and Objects-SOLUTION.ipynb 8

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01_Self_test_obj.ipynb 01_Self_test_obj.ipynb 11

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L15_Inheritance_in_Python.pptx L15_Inheritance_in_Python.pptx 12

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L16_Polymorphysim in Python.pptx L16_Polymorphysim in Python.pptx 13

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Context Module Sub Header

P15_Write a program to show the OOPS concepts: Inheritance 14

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P16_Write a program to show the OOPS concepts: Polymorphism 15

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External Url

Self Learning Module Self Learning Module 16

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01_Self_tes_modular-soln.ipynb 01_Self_tes_modular-soln.ipynb 17

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01_Self_test_modular.ipynb 01_Self_test_modular.ipynb 18

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External Url

Feedback Module:3 Feedback Module:3 20

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Assignment

Assignment: Object-Oriented Programming for Python Assignment: Object-Oriented Programming for Python 10 21

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Unit 4: Data Manipulation using Pandas

Unit 4: Data Manipulation using Pandas Unit 4: Data Manipulation using Pandas

Context Module Sub Header

Week 9 1

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External Url

Pandas Package Documentation Pandas Package Documentation 2

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L17_Pandas for Data Analysis.pptx L17_Pandas for Data Analysis.pptx 3

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Attachment

Creating Series List, array in pandas.pptx Creating Series List, array in pandas.pptx 4

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01_Notebook_Series.ipynb 01_Notebook_Series.ipynb 5

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Context Module Sub Header

P17_MID_TERM VIVA 6

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Context Module Sub Header

P18_MID TERM VIVA 7

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Context Module Sub Header

WEEK 10 8

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Page

L21_Operations on Data Frame L21_Operations on Data Frame 9

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02_Notebook_DataFrames.ipynb 02_Notebook_DataFrames.ipynb 10

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03_Notebook_Missing Data.ipynb 03_Notebook_Missing Data.ipynb 11

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P19_Import csv, excel, html etc using Pandas and also convert dictionary to dataframe etc. 12

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P20_To create and perform operations on Pandas Dataframe using Failed bank Dataset. 13

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Week 11 14

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L19_Filtering, Manipulating Index, Multi-Index and Index Hierarchy.ipynb L19_Filtering, Manipulating Index, Multi-Index and Index Hierarchy.ipynb 15

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L20_Imputation, Grouping and aggregation, Merging, Joining, Concatenation, Info on Unique Values L20_Imputation, Grouping and aggregation, Merging, Joining, Concatenation, Info on Unique Values 16

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04_Notebook_Groupby.ipynb 04_Notebook_Groupby.ipynb 17

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05_Notebook_Merging Joining and Concatenating.ipynb 05_Notebook_Merging Joining and Concatenating.ipynb 18

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Context Module Sub Header

P21_Perform Data Analysis using Pandas on Failed bank Dataset. 19

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P22_Demonstrate the Data Frame Operations and Missing Values on Iris Data 20

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Quiz

Quiz4: Data Analysis using Pandas Quiz4: Data Analysis using Pandas 10 21

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Unit 5: Data Visualization in Python (in progress)

Unit 5: Data Visualization in Python (in progress) Unit 5: Data Visualization in Python (in progress)

Context Module Sub Header

Week 12 1

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External Url

L23_Installing and setting up visualization libraries, plots L23_Installing and setting up visualization libraries, plots 2

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External Url

L23_Installing Matplotlib L23_Installing Matplotlib 3

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L24_scatter, histogram, boxplot, Logarithmic scale, Placement of ticks and custom tick labels, Pandas Viz, Style Sheets, Plot type, Area,.ipynb L24_scatter, histogram, boxplot, Logarithmic scale, Placement of ticks and custom tick labels, Pandas Viz, Style Sheets, Plot type, Area,.ipynb 4

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P23_Perform data processing with Pandas and Matplotlib library on Company Sales Dataset. 5

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Context Module Sub Header

P24_Practice on Studied plots using publicly available datasets 6

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Week 13 7

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Attachment

L25_Advanced Matplotlib Concepts.ipynb L25_Advanced Matplotlib Concepts.ipynb 8

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Attachment

L26_Hexagonal Bin Plot, Kernel Density Estimation plot (KDE), Distribution Plots, jointplot, pairplot, rugplot, kdeplot,.ipynb L26_Hexagonal Bin Plot, Kernel Density Estimation plot (KDE), Distribution Plots, jointplot, pairplot, rugplot, kdeplot,.ipynb 9

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Context Module Sub Header

P25_Perform visualization using Seaborn library of Python on Company Sales Dataset. 10

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Context Module Sub Header

P26_Practice on Studied plots using publicly available datasets 11

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Context Module Sub Header

Week 14 12

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Attachment

L27_Categorical Data Plots, barplot and countplot, countplot, boxplot VS violinplot,.ipynb L27_Categorical Data Plots, barplot and countplot, countplot, boxplot VS violinplot,.ipynb 13

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Context Module Sub Header

L28_stripplot and swarmplot, Combining Categorical Plots, 14

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Context Module Sub Header

P27-P28: Project Evaluation 15

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Context Module Sub Header

Week 15 16

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Attachment

L29_factorplot, Matrix Plots, Heatmap, clustermap, Regression Plots, Funcions associated with different plots,.ipynb L29_factorplot, Matrix Plots, Heatmap, clustermap, Regression Plots, Funcions associated with different plots,.ipynb 17

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Attachment

L30_Grids, PairGrid, pairplot, Facet Grid, JointGrid, Color..ipynb L30_Grids, PairGrid, pairplot, Facet Grid, JointGrid, Color..ipynb 18

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Quiz

Quiz5: Data Visualization using Different Plots Quiz5: Data Visualization using Different Plots 10 20

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Assignment

Lab Manual Endterm Lab Manual Endterm 20 21

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Assignment

Endterm Project Submission DS-IIIA Endterm Project Submission DS-IIIA 30 22

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Quiz

PFDS Quiz for students who missed quiz earlier PFDS Quiz for students who missed quiz earlier 10 23

quiz 32338 1

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Module 0: Big Data CSL 311

Module 0: Big Data CSL 311 Module 0: Big Data CSL 311

Attachment

CSl311_BigData_Revised_Cintana.docx CSl311_BigData_Revised_Cintana.docx 1

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Attachment

Introduction to course Introduction to course 2

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Attachment

Hadoop For Dummies - Dirk deRoos 2014.pdf Hadoop For Dummies - Dirk deRoos 2014.pdf 3

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Attachment

HadoopBook.pdf HadoopBook.pdf 4

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Attachment

pyspark.pdf pyspark.pdf 5

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Attachment

Sams Teach Yourself Hadoop in 24 Hours.epub Sams Teach Yourself Hadoop in 24 Hours.epub 6

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Attachment

mrjob.pdf mrjob.pdf 7

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Attachment

lab manual.BigDataCSL_311.docx lab manual.BigDataCSL_311.docx 8

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Assignment

Practical File Section A Practical File Section A 10 9

assignment 147700 1

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Assignment

Practical File Section B Practical File Section B 10 10

assignment 147701 1

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Assignment

PracticalFile_DS7 PracticalFile_DS7 0 11

assignment 147702 1

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Module 1: Introduction to Big Data & Google Cloud Platform

Module 1: Introduction to Big Data & Google Cloud Platform Module 1: Introduction to Big Data & Google Cloud Platform

Context Module Sub Header

Introduction to Big Data 1

context_module_sub_header 147703 0

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Attachment

L1 Introduction to Big Data.pptx L1 Introduction to Big Data.pptx 2

attachment 147704 0

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External Url

L1 Introduction to Big Data( You Tube Video) L1 Introduction to Big Data( You Tube Video) 3

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Attachment

L2 Challenges & Applications of Big Data.pptx L2 Challenges & Applications of Big Data.pptx 4

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External Url

L2 Big Data Applications(Video) L2 Big Data Applications(Video) 5

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Context Module Sub Header

Introduction to Google Cloud Platform 6

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Attachment

L3 Understanding GCP & its Services.pptx L3 Understanding GCP & its Services.pptx 7

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Attachment

L4 Google storage services & Big Query.pptx L4 Google storage services & Big Query.pptx 8

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External Url

L3/L4 Introduction to GCP ( Video Tutorials) L3/L4 Introduction to GCP ( Video Tutorials) 9

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Context Module Sub Header

Practicals ( P1-P3) 10

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Page

Coursera Course Link Coursera Course Link 11

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Context Module Sub Header

Study Material 12

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Attachment

Big-Data-3-Platform-Elements-Virtualization.pdf Big-Data-3-Platform-Elements-Virtualization.pdf 13

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Attachment

Big Data.pptx Big Data.pptx 14

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Attachment

Big-Data-4-Platform-Elements-Cloud-Computing.pdf Big-Data-4-Platform-Elements-Cloud-Computing.pdf 15

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Context Module Sub Header

Assignment 16

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Assignment

Assignment 1-Unit 1 (ungraded) Assignment 1-Unit 1 (ungraded) 5 17

assignment 147719 1

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Context Module Sub Header

Quiz 18

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Quiz

Quiz 1- Unit 1 ( Kahoot Quiz) :Ungraded Quiz 1- Unit 1 ( Kahoot Quiz) :Ungraded 4 19

quiz 147721 1

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Context Module Sub Header

Discussion 20

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Discussion Topic

What is Big Data ? Discuss the various V's of Big Data What is Big Data ? Discuss the various V's of Big Data 21

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Module 2 : Hadoop Architecture and fundamentals

Module 2 : Hadoop Architecture and fundamentals Module 2 : Hadoop Architecture and fundamentals

External Url

What is Hadoop(You Tube Video) What is Hadoop(You Tube Video) 1

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Attachment

L5 Apache Hadoop & its architecture.pptx L5 Apache Hadoop & its architecture.pptx 2

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Attachment

L6 Apache Hadoop Fundamentals.pptx L6 Apache Hadoop Fundamentals.pptx 3

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External Url

Hadoop Ecosystem( You Tube Video) Hadoop Ecosystem( You Tube Video) 4

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Attachment

L7 Apache Hadoop on Google Cloud Platform.pptx L7 Apache Hadoop on Google Cloud Platform.pptx 5

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Attachment

L8 Apache Hadoop & Its Ecosystem.pptx L8 Apache Hadoop & Its Ecosystem.pptx 6

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External Url

Hadoop 1.0 V/s Hadoop 2.0(You tube Tutorial) Hadoop 1.0 V/s Hadoop 2.0(You tube Tutorial) 7

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Context Module Sub Header

Practicals 8

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Page

P4 & P5 Installation of Hadoop on Windows/mac P4 & P5 Installation of Hadoop on Windows/mac 9

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Page

P6 & P7 Learning HDFS Commands P6 & P7 Learning HDFS Commands 10

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Context Module Sub Header

Study Material 11

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Attachment

Big-Data-7-Hadoop-1-and-2.pdf Big-Data-7-Hadoop-1-and-2.pdf 12

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Context Module Sub Header

Assignment 13

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Quiz

Quiz1(CO1 &CO2) Quiz1(CO1 &CO2) 12 15

quiz 147738 1

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Quiz

Quiz1_Unit1&2_SectionD Quiz1_Unit1&2_SectionD 10 16

quiz 147739 1

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Discussion Topic

Is Hadoop an obsolete system? Is Hadoop an obsolete system? 18

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Module 3 : Map Reduce Architecture & Programming

Module 3 : Map Reduce Architecture & Programming Module 3 : Map Reduce Architecture & Programming

Context Module Sub Header

Map Reduce Programming 1

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External Url

Map Reduce Concepts( You Tube Video) Map Reduce Concepts( You Tube Video) 2

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Attachment

L9/L10 Map Reduce Programming.pptx L9/L10 Map Reduce Programming.pptx 3

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Attachment

L 11/L12 Map Reduce Programming (3).pptx L 11/L12 Map Reduce Programming (3).pptx 4

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Attachment

mapreduce in python.pptx mapreduce in python.pptx 5

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Context Module Sub Header

Practical Drills( P9-P12) 6

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Attachment

Map_reduce1.pdf Map_reduce1.pdf 7

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Attachment

mapreduce2.pdf mapreduce2.pdf 8

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Attachment

mapreduce3 (1).pdf mapreduce3 (1).pdf 9

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Attachment

mapreduce4.pdf mapreduce4.pdf 10

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Attachment

mapreduce5.pdf mapreduce5.pdf 11

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Attachment

crawl_result.tsv crawl_result.tsv 12

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Context Module Sub Header

Study Material 14

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Attachment

Map Reduce Programming (ASU Content).pdf Map Reduce Programming (ASU Content).pdf 15

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Quiz

QUIZ2(CO3)_Section B QUIZ2(CO3)_Section B 10 17

quiz 147758 1

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Quiz

Quiz2_Unit3_SectionD Quiz2_Unit3_SectionD 10 18

quiz 147759 1

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Module 4 : Pig & Hive

Module 4 : Pig & Hive Module 4 : Pig & Hive

Context Module Sub Header

PIG COMMANDS(Ref Chapter 16 of HadoopBook in module 0) 1

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Attachment

Apache Pig.pptx Apache Pig.pptx 2

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Attachment

apache_pig_nasics.pdf apache_pig_nasics.pdf 3

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Attachment

cogroup_Pig.jpeg cogroup_Pig.jpeg 4

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Attachment

commands_summary.jpeg commands_summary.jpeg 5

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Attachment

file_system_commands_pig.jpeg file_system_commands_pig.jpeg 6

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Attachment

flatten_pig.jpeg flatten_pig.jpeg 7

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Attachment

utility_commands_pig.jpeg utility_commands_pig.jpeg 8

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External Url

Apache Basics URL Apache Basics URL 9

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Attachment

PIG_CHAPTER.rar PIG_CHAPTER.rar 10

attachment 147769 0

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Context Module Sub Header

PIG SCRIPT EXAMPLES 11

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Attachment

Pig Functions and Paramerters.pig Pig Functions and Paramerters.pig 12

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Attachment

Titanic.csv Titanic.csv 13

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Attachment

titanic_script.docx titanic_script.docx 14

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Context Module Sub Header

FILE FORMATS AND HIVE 15

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Attachment

Chapter for Hive.pdf Chapter for Hive.pdf 16

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Attachment

File Formats in Hadoop.pptx File Formats in Hadoop.pptx 17

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Attachment

HIVE_FINAL.pptx HIVE_FINAL.pptx 18

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Context Module Sub Header

HIVE SCRIPTS EXAMPLES 19

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Attachment

emp.txt emp.txt 20

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Attachment

employee_contract.txt employee_contract.txt 21

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employee_hr.txt employee_hr.txt 22

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employee_id.txt employee_id.txt 23

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Attachment

hive_queries.txt hive_queries.txt 24

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json_xml_read_hive.docx json_xml_read_hive.docx 25

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wordcount.hql wordcount.hql 26

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Assignment

ASSIGNMENT_PIG_HIVE_SectionA ASSIGNMENT_PIG_HIVE_SectionA 10 27

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Assignment

ASSIGNMENT_PIG_HIVE_SectionD ASSIGNMENT_PIG_HIVE_SectionD 10 28

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Module 5 : Spark Architecture & Spark Programming

Module 5 : Spark Architecture & Spark Programming Module 5 : Spark Architecture & Spark Programming

Attachment

Spark Programming Basics.pptx Spark Programming Basics.pptx 1

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Attachment

spark_sql.pptx spark_sql.pptx 2

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Context Module Sub Header

python notebooks for Spark 3

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Attachment

Introduction_RDD_examples (1).ipynb Introduction_RDD_examples (1).ipynb 4

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Attachment

Basic_tranformations (1).ipynb Basic_tranformations (1).ipynb 5

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Dates_and_Timestamps (1).ipynb Dates_and_Timestamps (1).ipynb 6

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Attachment

Missing_Data (1).ipynb Missing_Data (1).ipynb 7

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Attachment

GroupBy_and_Aggregate_Functions (1).ipynb GroupBy_and_Aggregate_Functions (1).ipynb 8

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Attachment

DataFrame_Basics (1).ipynb DataFrame_Basics (1).ipynb 9

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Attachment

DataFrame_Basic_Operations (1).ipynb DataFrame_Basic_Operations (1).ipynb 10

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Attachment

Spark DataFrames Project Exercise.ipynb Spark DataFrames Project Exercise.ipynb 11

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Attachment

Linear_Regression_Example (1).ipynb Linear_Regression_Example (1).ipynb 12

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Attachment

Linear_Regression_Code_Along (1).ipynb Linear_Regression_Code_Along (1).ipynb 13

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Attachment

Logistic_Regression_Example (1).ipynb Logistic_Regression_Example (1).ipynb 14

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Attachment

Titanic_Log_Regression_Code_Along (1).ipynb Titanic_Log_Regression_Code_Along (1).ipynb 15

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Attachment

Clustering_Code_Example (1).ipynb Clustering_Code_Example (1).ipynb 16

attachment 147803 0

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Attachment

apple.csv apple.csv 17

attachment 147804 0

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Attachment

college.csv college.csv 18

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Attachment

Ecommerce_Customers.csv Ecommerce_Customers.csv 19

attachment 147806 0

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Attachment

fake_customers.csv fake_customers.csv 20

attachment 147807 0

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Attachment

seeds_dataset.csv seeds_dataset.csv 21

attachment 147808 0

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Attachment

titanic.csv titanic.csv 22

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Attachment

walmart_stock.csv walmart_stock.csv 23

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adventures.txt adventures.txt 24

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Quiz

quiz3_spark_section A quiz3_spark_section A 10 25

quiz 147812 1

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Quiz

quiz3_spark_section B quiz3_spark_section B 10 26

quiz 147813 1

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete

Course Modules

Introduction to the Course

Unit 1: Basics of Python Programming

Week 1 1

L01_Evaluation Scheme and Rubrics 2

L02_Introduction To Python 3

P01_Installation of Python IDE Anconda and Set-up Jupyter Notebook 7

P02_Explore the Jupyter Notebook and Spyder with basics commands of python 8

Week 2: Basic Operations and Data Types 10

L04_Control Structures and Decision 14

P03_Expressions_Variables_Datatypes_in_Python. 17

P04_program to print each letter of a word. Repeat this process for atleast five words 21

Week 3 22

L05_Loops in Python 23

P05_Study of Python commands for List 27

P06_commands to find length of the list and check if a fruit exists in the list, create copy of the list. 28

Unit 2: Collections and Functions

Week 4: Dictionary and Array in Python 9

P09_Give commands to create a dictionary of brand, model and year, access a specific item, change value of any one item 25

P10_Check prime and Armstrong number by making functions. 26

Unit 3: Object Oriented Concepts for Python

Week 7: Class and Objects 1

P13_Create a class “Person” with atleast five attributes. Create five objects and display. 6

P14_Write a program to show the OOPS concepts: Encapsulation 7

P15_Write a program to show the OOPS concepts: Inheritance 14

P16_Write a program to show the OOPS concepts: Polymorphism 15

Unit 4: Data Manipulation using Pandas

Week 9 1

P17_MID_TERM VIVA 6

P18_MID TERM VIVA 7

WEEK 10 8

P19_Import csv, excel, html etc using Pandas and also convert dictionary to dataframe etc. 12

P20_To create and perform operations on Pandas Dataframe using Failed bank Dataset. 13

Week 11 14

P21_Perform Data Analysis using Pandas on Failed bank Dataset. 19

P22_Demonstrate the Data Frame Operations and Missing Values on Iris Data 20

Unit 5: Data Visualization in Python (in progress)

Week 12 1

P23_Perform data processing with Pandas and Matplotlib library on Company Sales Dataset. 5

P24_Practice on Studied plots using publicly available datasets 6

Week 13 7

P25_Perform visualization using Seaborn library of Python on Company Sales Dataset. 10

P26_Practice on Studied plots using publicly available datasets 11

Week 14 12

L28_stripplot and swarmplot, Combining Categorical Plots, 14

P27-P28: Project Evaluation 15

Week 15 16

Module 0: Big Data CSL 311

Module 1: Introduction to Big Data & Google Cloud Platform

Introduction to Big Data 1

Introduction to Google Cloud Platform 6

Practicals ( P1-P3) 10

Study Material 12

Assignment 16

Quiz 18

Discussion 20

Module 2 : Hadoop Architecture and fundamentals

Practicals 8

Study Material 11

Assignment 13

Module 3 : Map Reduce Architecture & Programming

Map Reduce Programming 1

Practical Drills( P9-P12) 6

Study Material 14

Module 4 : Pig & Hive

PIG COMMANDS(Ref Chapter 16 of HadoopBook in module 0) 1

PIG SCRIPT EXAMPLES 11

FILE FORMATS AND HIVE 15

HIVE SCRIPTS EXAMPLES 19

Module 5 : Spark Architecture & Spark Programming

python notebooks for Spark 3