Data Analytics with Python

This course will enable you to learn the core concepts of programming in Python and thus will become eligible to apply for the positions in top companies like Google, Microsoft and more. It is designed in such a way you learn the python language and dig into data analysis and data which is popular packages like pandas, query databases with SQL and more. The best way to learn is by doing, and in this course you will learn the concepts and challenge yourself in improving your data analysis skills. The core idea is to learn how to manipulate and analyze data.


Who is Data Analytics with Python course for?

This course can be taken up by Software Developers and BI and Analytics, ETL, SQL, Data Warehouse, Mainframe, and Testing Professionals.


Agenda/ Schedule of Training

  • Basic and intermediate programming concepts
  • How to clean and visualize data.
  • Probability and statistics for data analysis.
  • Collaboration tools like git and SQL databases.
  • Use different data aggregation techniques.
  • Combine data sets.
  • Transform and reshape data.
  • Clean strings and handle missing data.


Week 1 - Introduction: Welcome and overview of the course. Introduction to the data science process and the value of learning data science.

Week 2 - Background: In this optional week, we provide a brief background in python or unix to get you up and running. 

Week 3 - Jupyter and Numpy: Jupyter notebooks are one of the most commonly used tools in data science as they allow you to combine your research notes with the code for the analysis. After getting started in Jupyter, we'll learn how to use NumPy for data analysis. NumPy offers many useful functions for processing data as well as data structures which are time and space efficient.

Week 4 - Pandas: Pandas, built on top of NumPy, adds data frames that offer critical data analysis functionality and features.

Week 5 - Visualization: When working with large datasets, you often need to visualize your data to gain a better understanding of it. Also, when you reach conclusions about the data, you'll often wish to use visualizations to present your results.

Week 6 - Mini Project: With the tools of Jupyter notebooks, numpy, pandas, and Visualization, you're ready to do sophisticated analysis on your own. You'll pick a dataset we've worked with already and perform an analysis for this first project.

Week 7 - Machine Learning: To take your data analysis skills one step further, we'll introduce you to the basics of machine learning and how to use sci-kit learn - a powerful library for machine learning.

Week 8 - Working with Text and Databases: You'll find yourself often working with text data or data from databases. This week will give you the skills to access that data. For text data, we'll also give you a preview of how to analyze text data using ideas from the field of Natural Language Processing and how to apply those ideas using the Natural Language Processing Toolkit (NLTK) library.

Week 9 and 10 - Final Project: These weeks let you showcase all your new skills in an end-to-end data analysis project. You'll pick the dataset, do the data munging, ask the research questions, visualize the data, draw conclusions, and present your results.

Python is a very popular language for data analysis. The number of libraries has increased and having a certificate in data analysis in python will boost your career. 




 What are the benefits of Data Analytics for Lean Six Sigma? 

The Data Analytics for Lean Six Sigma certification will enhance your career opportunities. It enables you to be recognized as a professional who has enough experience in the field of project management and data analysis. You will learn many new skills that will enhance your knowledge in the field. The certification also enables you to earn more.

How can I prepare for the Exam?

Make sure to use a good Data Analytics for Lean Six Sigma preparation book to build your confidence and knowledge towards the exam. You can also try Data Analytics for Lean Six Sigma exam prep workshops and online practice exams.

When can I take the exam?

You can take the exam whenever you are ready, all you need to do is schedule a date from the nearest PMP test center.

Can I retake the exam if I fail?

Yes, if you fail in your first attempt, you can retake the exam for up to two more times within the one year eligibility period.

How much salary will I get after doing this course?

Based on research and analysis, it is seen that Data Analytics for Lean Six Sigma professionals seem to earn 30% more than non-certified professionals in the field of project management.

Is Data Analytics for Lean Six Sigma really worth it?

Yes, it helps to improve your career and your job prospects. It boosts your chances to land a job and also make you much more valued.

Will Data Analytics for Lean Six Sigma help me get my dream job?

Yes, this depends if your dream job is one in the field of project management and data analysis as the Data Analytics for Lean Six Sigma is a certification that enhances your chances in the project management scene.

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