Data Analytics Real World Projects using Python

Data Analytics Real World Projects using Python, available at $54.99, has an average rating of 4.2, with 57 lectures, based on 41 reviews, and has 4250 subscribers.

You will learn about Boost your resume by learning real-world skills Get a job as a data Analyst/scientist with Python Take your career to the next level Use Python to solve real-world tasks This course is ideal for individuals who are If u are Aspiring data scientists or even if u are a learner or People interested in Data Analytics & who want to take their carrier to next level It is particularly useful for If u are Aspiring data scientists or even if u are a learner or People interested in Data Analytics & who want to take their carrier to next level.

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Summary

Title: Data Analytics Real World Projects using Python

Price: $54.99

Average Rating: 4.2

Number of Lectures: 57

Number of Published Lectures: 53

Number of Curriculum Items: 57

Number of Published Curriculum Objects: 53

Original Price: ?799

Quality Status: approved

Status: Live

What You Will Learn

Boost your resume by learning real-world skills

Get a job as a data Analyst/scientist with Python

Take your career to the next level

Use Python to solve real-world tasks

Who Should Attend

If u are Aspiring data scientists or even if u are a learner

People interested in Data Analytics & who want to take their carrier to next level

Target Audiences

If u are Aspiring data scientists or even if u are a learner

People interested in Data Analytics & who want to take their carrier to next level

Can you start right now?

A frequently asked question of Python Beginners is: “Do I need to become an expert in Python coding before I can start working on Data Analysis Projects?”

The clear answer is: “No!

You just require some Python Basics like data types, simple operations/operators, lists and numpy arrays

As a Summary, if you primarily want to use Python for Data Science or as a replacement for Excel, then this course is a perfect match!

Why should you take this Course?

It explains Projects on  real Data and real-world Problems. No toy data! This is the simplest & best way to become a Data Analyst/Data Scientist

It shows and explains the full real-world Data. Starting with importing messy data, cleaning data, merging and concatenating data, grouping and aggregating data, Exploratory Data Analysis through to preparing and processing data for Statistics, Machine Learning and Data Presentation.

It gives you plenty of opportunities topractice and code on your own. Learning by doing.

In real-world projects, coding and the business side of things are equally important. This is probably the only course that teaches both: in-depth Python Coding and Big-Picture Thinking like How you can come up with a conclusion

Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Course & its Benefits

Lecture 2: Utilize QnA Section ( Golden Opportunity ) !

Lecture 3: Basics of Jupyter Notebook !

Chapter 2: Introduction to Life-Cycle of Data Analytics Project

Lecture 1: First Stage : Business Understanding in Real World

Lecture 2: Second Stage : What is ETL (Extract ,Transform,Load) Pipeline ?

Lecture 3: Third Stage : EDA(Exploratory Data Analysis) + Conclusions

Chapter 3: Project 1: Job Market (Naukri.com) Data Analysis

Lecture 1: Introduction to Data & Business Problem !

Lecture 2: Datasets & resources

Lecture 3: Understand high-level Overview of Real-World

Lecture 4: Understanding your features more..

Lecture 5: Lets clean Payrate feature

Lecture 6: Other ways to clean Payrate feature

Lecture 7: Perform Feature Engineering on Payrate feature

Lecture 8: Lets perform Data cleaning on experience feature..

Lecture 9: Lets perform featurization on experience feature..

Lecture 10: Perform Feature Engineering On postdate feature..

Lecture 11: Prepare Job_location feature

Lecture 12: Lets make our data ready.

Lecture 13: Lets perform Descriptive statistics on Data..

Lecture 14: What are different types of Analysis?

Lecture 15: Lets Perform bi-variate analysis

Lecture 16: How to Automate your Code !

Lecture 17: How to make your code readible using DOCSTRING !

Lecture 18: Perform In-Depth Analysis on Data !

Lecture 19: Analyse relationship between data !

Lecture 20: What are Top rated skills ?

Lecture 21: Analysing available position in the industry.

Chapter 4: Project 2: Russian Tweets Data Analysis

Lecture 1: Datasets & Resources

Lecture 2: Understanding High-level Overview of data !

Lecture 3: Understand Trend of data !

Lecture 4: Preparing your Data For analysis -Part 1

Lecture 5: Preparing your Data For analysis -Part 2

Lecture 6: Preparing your Data For analysis -Part 3

Lecture 7: Analyse Whether tweets impact the way of the US elections or not !

Lecture 8: Analysing the percentage change in tweet counts

Lecture 9: Understand your Text feature well..

Lecture 10: How to Remove Re-tweet mentions from data.

Lecture 11: Remove Hyper-links from data

Lecture 12: Remove Hashtags from data..

Lecture 13: Remove User-mentions from data..

Lecture 14: How to extract user-mentions from data !

Lecture 15: How to extract hashtags from Data !

Chapter 5: Project 3: Super-Market Sales Data Analysis

Lecture 1: Datasets & Resources

Lecture 2: Lets Pre-process Data !

Lecture 3: How to Fetch derived attributes from data..

Lecture 4: Perform Descriptive analysis on Data..

Lecture 5: Lets Explore Data !

Lecture 6: Lets Define our own custom functions..

Lecture 7: Analysing Relationship in Data !

Lecture 8: Lets Perform Product-based Analysis

Lecture 9: Analyse whether customer type influences the sales or not ?

Lecture 10: Analysing Most favourite products of users..

Chapter 6: Bonus lecture

Lecture 1: Bonus section

Instructors

Shan Singh
Top Rated & Best-Selling Udemy Instructor , Data Scientist

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 8 votes

4 stars: 14 votes

5 stars: 19 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!