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    Data Analytics Real-World Projects in Python

    Requirements

    • You will need to install Anaconda. We will show you how to do it in one of the first lectures of the course

    Description

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

    Student Testimonials:

    • Excellent Course for Data Analytics Real World Projects.. specially in Python. Recommended Course for those who want to start or transform their career in Data Analytics- Alokkumar Mahato
    • I love how in 6 projects I went to 0 to 100% of knowledge of how to use some libraries and how to interpretate the results ! Also all my questions were answered ! Amazin course 110/100 – María Fernanda Villegas CascoU
    • The course was really helpful in learning data cleaning, data manipulation and data visualization. Newer library of plotly was something very new to me. while practizing with the dataset I got to know the pros of using plotly (simple, clear and interactive plots). Overall the coverage of the course with dataset from various industries and their problem set was very comprehensive and I think would match the industry scenario well. Also, I learned a whole new plethora of methods that are being called on class objects which I wasn’t familiar with before taking this course.Thanks for your support in Q&A as well.- Abhishek Gajbhiye

    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 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 datacleaning 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.
    • Professionals who are exposed to data but can’t yet leverage its power
    • Product managers who want to make data-driven decisions
    • It gives you plenty of opportunities to practice 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.

    Who this course is for:

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


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