Data Analysis Real world use-cases- Hands on Python

Build a Portfolio of 5 Data Analysis Projects with Python, Seaborn,Pandas,Plotly, numpy etc & get a job of Data Analyst

Ratings: 4.47 / 5.00




Description

This is the first course that gives hands-on Data Analysis Projects using Python..


Student Testimonials:


Shan Singh is absolutely amazing! Step-by-step projects with clear explanations. Easy to understand. Real-world  Data Analysis projects. Simply the best course on Data Analysis that I could find on Udemy! After the course you can easily start your career as a Data Analyst.- Nicholas Nita


This is the best course for people who have just learnt python basics(prerequisite for this course) and want to become Data Analyst/Data Scientist. This will act as bridge between fundamental theoretical python syntax to its application by using most important data analysis packages(Pandas, Matplotlib, Plotly etc). - Mirza Hyder Baig


Very good course, on one side the instructor elaborates on technic general knowledge like what is integer (signed/un-signed and what it contains) on the other side he is very short and to the chase with the python commands and the requirements execution flow - Tal Ioffe


superb. .. what a good soul he is ...his voice is filled with love and humbleness and understanding....he knows the pains of a begineer ...when he explains it fells like he is explaining to a 5 year old kid.... -





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 that you can learn from my Free Python course 'Basics Of Python'

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




Why should you take this Course?

  • It explains Real-world Data Analysis Projects on  real Data . 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, Data Analysis , Machine Learning and Data Presentation.


  • It gives you plenty of opportunities to practice and code on your own. Learning by doing.

  • In real-world Data Analysis 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 by doing Data Analysis ..

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


What You Will Learn!

  • Get a job as a data Analyst on an average $156,000 after showcase these Projects on your Resume
  • By the end of this course you will understand the inner workings of the data analytics pipeline -joining,manipulating,filtering, extracting data ,Analysing Data
  • Solve any problem in your business, job or in real-time with powerful data analysis libraries
  • you will expertise in Pandas , Numpy , Seaborn, Matplotlib , Plotly ,Folium, Geopy , Wordcloud , re and many other..
  • Learn how to work with various data within python, including: Excel Data,Geographical data,Text Data and Time Series Data Data
  • Solve any problem in your business, job or in real-time with powerful data analysis libraries

Who Should Attend!

  • Everyone who want to step into Data Science/Data Analytics.
  • Anyone interested about the rapidly expanding world of data Analytics/Data Science
  • Data Scientists/Data Analyst who want to improve their Data Handling/Manipulation/Analysis skills.
  • Anyone who want to switch Data Projects from Excel to Python (e.g. in Research/Science)
  • Excel users looking to learn a more powerful software for data analysis