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Description About The Course

Hi, dear learning aspirants welcome to “Ultimate Python Bootcamp For Data Science & Machine Learning ” from beginner to advanced level. We love programming. Python is one of the most popular programming languages in today’s technical world. Python offers both object-oriented and structural programming features. Hence, we are interested in data analysis with Pandas in this course. 

This course is for those who are ready to take their data analysis skill to the next higher level with the Python data analysis toolkits, i.e. "Pandas" and "NumPy".

This tutorial is designed for beginners and intermediates but that doesn't mean that we will not talk about the advanced stuff as well. Our approach of teaching in this tutorial is simple and straightforward, no complications are included to make bored Or lose concentration. In this tutorial, I will be covering all the basic things you'll need to know about the 'Pandas' to become a data analyst or data scientist.   

We are adopting a hands-on approach to learn things easily and comfortably. You will enjoy learning as well as the exercises to practice along with the real-life projects (The projects included are the part of large size research-oriented industry projects).

What you will learn:

You will become a specialist in the following things while learning via this course

“Data Analysis With Pandas”.

  • You will be able to analyze a large file

  • Build a Solid Foundation in Data Analysis with Python

After completing the course you will have professional experience on;

  • Pandas Data Structures: Series, DataFrame and Index Objects

  • Essential Functionalities

  • Data Handling

  • Data Pre-processing

  • Data Wrangling

  • Data Grouping

  • Data Aggregation

  • Pivoting

  • Working With Hierarchical Indexing

  • Converting Data Types

  • Time Series Analysis

  • Advanced Pandas Features and much more with hands-on exercises and practice works.

Who this course is for:

  • Beginner Python developers - Curious to learn about Data Science Or Data Analysis
  • Data Analysis Beginners
  • Aspiring data scientists who want to add Python to their tool arsenal
  • Students and Other Professionals
  • AI and ML aspirants to upgrade their knowledge in Data Preprocessing before applying the machine learning algorithms to their projects
  • Data Analyst job seekers who wants to update their Resume with Python's data analysis toolkit

Course Curriculum: Duration 18 Hours

  • 1

    Welcome To The Course!

    • From Thinkific Team: How To Use This Course
  • 2

    NumPy Tutorial: Complete Basics To Advance Level

    • NumPy For Every Data Analyst

    • 00 What Is Numpy?

    • NumPy Course Materials

    • 01 How To Install And Setup Numpy & Pandas

    • 02 Numpy Initialization

    • 03 Creating An Nd-arrays

    • 04 Data Types

    • 05 Pseudorandom Number Generation

    • 06 Arithmetic Operations

    • 07 Indexing And Slicing

    • 08 Boolean Indexing

    • 09 Fancy Indexing

    • 10 Universal Functions In Numpy

    • 11 Conditional Logics In Numpy

    • 12 Mathematical & Statistical Methods

    • 13 Methods Applied To Boolean Arrays

    • 14 Sorting In Numpy

    • 15 Unique And Set Logic In Numpy

    • 16 How To Save And Load In Numpy

    • 17 Linear Algebra In Numpy
  • 3

    Welcome To The Course ! Ultimate Pandas For Data Science & Machine Learning

    • Welcome To Pandas Tutorial

    • Resource Files: Ultimate Pandas For Data Science and Machine Learning
  • 4

    Getting Started

    • 18 Course Introduction

    • 19 How To Get Most Out Of This Course

    • 20 Better To Know These Things

    • 21 How To Install Python IPython And Jupyter Notebook

    • 22 How To Install Anaconda For MacOS And Linux Users

    • 23 How To Work With The Jupyter Notebook Part 1

    • 24 How To Work With The Jupyter Notebook Part 2
  • 5

    Pandas Building Blocks

    • 25 How To Work With The Tabular Data

    • 26 How To Read The Documentation In Pandas
  • 6

    Pandas Data Structures

    • 27 Theory On Pandas Data Structures

    • 28 How To Construct The Pandas Series

    • 29 How To Construct The DataFrame Objects

    • 30 How To Construct The Pandas Index Objects

    • 31 Practice Part 1

    • 32 Practice Part 1 Solution
  • 7

    Data Indexing And Selection

    • 33 Theory On Data Indexing And Selection

    • 34 Data Selection In Series Part 1

    • 35 Data Selection In Series Part 2

    • 36 Data Selection In DataFrame Part 1

    • 37 Data Selection In DataFrame Part 2

    • 38 Accessing Values Using Loc Iloc And Ix In DataFrame Objects

    • 39 Indexers Loc And Iloc In Series

    • 40 Practice Part 2

    • 41 Practice Part 2 Solution
  • 8

    Essential Functionalities

    • 42 Theory On Essential Functionalities

    • 43 How To Reindex Pandas Objects

    • 44 How To Drop Entries From An Axis

    • 45 Arithmetic And Data Alignment

    • 46 Broadcasting In Pandas

    • 47 How To Work With The Duplicated Indices

    • 49 Summarizing And Computing Descriptive Statistics

    • 48 Apply And Apply map In Pandas

    • 50 Unique Values Value Counts And Membership

    • 51 How To Sort And Rank In Pandas

    • 52 Arithmetic Methods With Fill Values

    • 53 Practice Part 3

    • 54 Practice Part 3 Solution
  • 9

    Data Handling

    • 55 Theory On Data Handling

    • 56 How To Read The Csv Files Part-1

    • 57 How To Read The Csv Files Part-2

    • 58 How To Read Text Files In Pieces

    • 59 How To Export Data In Text Format

    • 60 How To Use Python's Csv Module

    • 61 Practice Part 4

    • 62 Practice Part 4 Solution
  • 10

    Data Cleaning And Preparation

    • 63 Theory On Data Preprocessing

    • 64 How To Filter The Missing Values Part 1

    • 65 How To Filter The Missing Values Part 2

    • 66 How To Remove Duplicate Rows And Values

    • 67 How To Replace The Non Null Values

    • 68 How To Rename The Axis Labels

    • 69 How To Discretize And Bin The Data

    • 70 How To Filter And Detect The Outliers

    • 71 How To Reorder And Select Randomly

    • 72 Converting The Categorical Variables Into Dummy Variables

    • 73 How To Use 'map' Method

    • 74 Using Regular Expressions

    • 75 How To Manipulate With Strings

    • 76 Working With The Vectorized String Functions

    • 77 Practice Part 5

    • 78 Practice Part 5 Solution
  • 11

    Data Wrangling

    • 79 Theory On Data Wrangling

    • 80 Hierarchical Indexing

    • 81 Summary Statistics By Level

    • 82 Hierarchical Indexing Reordering And Sorting

    • 83 Hierarchical Indexing With DataFrame Columns

    • 84 How To Concatenate Along An Axis

    • 86 Merging On Row Index

    • 85 How To Merge The Pandas Objects

    • 87 How To Combine With Overlap

    • 89 How To Reshape And Pivot Data In Pandas

    • 90 Practice Part 6

    • 91 Practice Part 6 Solution
  • 12

    Data Grouping and Aggregation

    • 92 Theory On Data Groupby And Aggregation

    • 93 Groupby Operation

    • 94 How To Iterate Over Groupby Object

    • 95 How To Select Columns In Groupby Method

    • 96 Grouping Using Dictionaries And Series

    • 97 Grouping Using Functions And Index Level

    • 98 Data Aggregation

    • 99Practice Part 7

    • 100 Practice Part 7 Solution
  • 13

    Time Series Analysis

    • 101 Theory On Time Series Analysis

    • 102 Introduction To Time Series Data Types

    • 104 Time Zone Handling

    • 105 How To Convert Between String And Datetime

    • 103 Date Ranges Frequencies And Shifting Part

    • 106 Time Series Basics With Pandas Objects

    • 107 Practice Part 8

    • 108 Practice Part 8 Solution
  • 14

    How To Analyse With The Part of Real Life Projects

    • 109 Pandas Project Section

    • 110 Project 1 Description

    • 112 Project 1 Solution Part 1

    • 113 Project 1 Solution Part 2

    • 114 Project 2 Description

    • 115 Project 2 Solution

    • 116 Project 3 Description

    • 117 Project 3 Solution Part 1

    • 118 Project 3 Solution Part 2

Know About Your Instructor:

Entrepreneur | Professional Educator & Software Trainer

Pruthviraja L

Hi, I am Pruthivraja L, with more than 7 plus years of teaching and training experience from various technical institutes. Teaching is my passion. I'm a Certified Data Analyst. I got certifications from various eLearning centers including Udemy, Intellipaat-Bengaluru, LinkedIn eLearning center, Coursera-IBM, Eduonix, Tutorialspoint, Tableau etc. My teaching skills are MATLAB, Python, SAS, R , Machine learning, Data Science and Data Analysis. I'm a multi faceted software professional aspirant with demonstrated capability in deploying analytical and programming methodologies to extract insights for boosting and bolstering user requirements. Adept at conducting statistical analysis and data modeling for transforming raw data into actionable strategies. I've written a student-friendly textbook in the electrical engineering field titled 'Elements of Electrical Engineering' under the publication of 'I.K. International Publishing House Pvt. Ltd', New Delhi, India. The book is available in many countries including the USA and UK via Amazon and many other seller portals. The book is now started distributing under Wiley India Pvt. Ltd.
Watch Intro Video

Watch Our Sample Project Solution For Industry Oriented Case Study Problem

Testimonials

These are The Testimonials From Previous Leaners From Previous Platforms Where We Have Taught

Great Effort

Kamalakannan kk

Thank you so much for this course by Mentor Mr. Pruthviraja L . Kudos to you. I was learning pandas for past 6 months, but I couldn't able to remember syntax for some basics. But , I continuously watched your videos for past 10 days and completed the course. Within 10 days, I am ready to do data analysis with pandas. One small correction : You should speak fast . Thank You Sir for your great effort. I'll surely recommend your course to someone who wants to learn data analysis with pandas. Once again, Thank You!

Simply Great

Sagar Kalbhor

I have recently completed Udemy course on python for data analysis with pandas It was simply great? I am a mechanical engineer but wanted to do career in data science And that course was simply great ? Thank you for an awesome course from basic to advanced.

Very Good

Rodda Ashok Kumar Reddy

This Course was very good. It is very useful for those who are entering for the training on Data Science Courses.

Awesome Course

kalpit Jindal

Very awesome course, I really liked it

Join The Course

You Are One Step Away To Become an Expert In Data Science. Never Miss This Opportunity!

Join this online course just by paying the course maintenance charge for regular updates. We ensure that, you definitely like our course and get high performance skill for Data Analysis & Data Science.
Enroll Now @ ₹59/-Only

Benefits Of Enrolling

Never Underestimate Your Mind Logic, It May Work Like An Ultimate Resource of Motivation!

  • Improves Your Coding Skill

    This course is full of practical approach, so you never get bored of walking with it and enjoy the way we used to code and see the developer level skill in yourself.

  • Build Strong Confidence

    Once you complete this course, you will get enough confidence to work the project of you own either internship or freelance work. And ready to face any challenging interviews on Data Science and Data Analysis Field.

  • Motivate Yourself

    Once you finish watching & working with the course, you'll get enough inspiration to take further courses related to Data Science field. You also get motivated to change your career in Data Science or ML or Data Analysis area if already not working on these domains.

FAQ's

  • What is special about your course?

    This course has been taught for more than 60K students all over the world in various platforms we have worked so far. And we felt like why can't we offer this course in a different platform at different price and freedom of learning at their own pace.

  • Why should I take this course?

    This is the ultimate and excellent resource to gain practical knowledge on Exploratory data analysis. This course is fully constructed with practical base unlike other courses, you will not worry about the project and practice exercises. You will really enjoy learning new skills of Pandas & NumPy to analyze your data in structured form.

  • Can I offer for refund?

    Though you're enrolled to an excellent resource to gain knowledge on new emerging technology of AI and Machine Learning, going away from this course makes us to regret you. But, if you really doesn't get satisfied with the course or the way we train, you are eligible to get you refund back except the transaction fee from that we neither benefit or profit.

You Get It All For Just ₹59/-Only. What are you waiting for?

Enroll to start learning with the practical work. We focus on practice and practical work, instead of giving only the rough theoretical ideas or presentations.

Get started now @ ₹59/- Only