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.
Enroll now: Data Analytics Real World Projects using Python
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!
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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?
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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
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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.
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It gives you plenty of opportunities topractice and code on your own. Learning by doing.
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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
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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
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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
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