The Data Analyst Bootcamp is upgraded to 2.0
Become a high paying AI enabled data analyst by learning the secrets of the industry taught by two data analyst hiring managers with 8+ years of international experience in data industry.
This course uses a project-based learning approach to teach you Python using two real-life projects (1) Hospitality domain data analysis and (2) Medical data extraction. Learning Python programming through projects helps you understand real-life applications of this awesome programming language. You will also have two solid projects that you can add to your resume and you work on end-to-end implementation. Total beginners, as well as people familiar with the language, will benefit from this Python course.
This practical beginner’s course lets you learn Power BI from scratch, preparing you for the data analyst, business analyst, or Power BI developer job market. The course provides an end-to-end Power BI project, carefully curated to offer you real organizational experience and business context.
Beginners to Advanced SQL course for those preparing for a data career (data analyst, data scientist, or data engineer). This course is carefully curated to simulate real-time organizational experience to prepare you for the current job market and at the same time provides you with an ultimate learning experience through a storytelling mode that you would see in movies.
Beginners to Advanced Excel course for those who are preparing for a data career (especially Data Analysts). This course is carefully curated by industry experts to mimic real-world scenarios to prepare you to become a market fit. You will also get practical exercises to practice and get a simulated experience of a data analyst using Excel to solve problems.
Learn the key concepts of Math and Statistics that lay the foundations for a strong data science career. This course is carefully curated to simulate real-time organizational experience to prepare you for the current job market and at the same time provides you with an ultimate learning experience through storytelling and intuitive explanations.
Potato Disease Classification End to end deep learning project Online in Codebasics. Learn to Classify disease in potato plants as either early blight or late blight.
Best way to learn Mathematics and Statistics for data science in Hindi. This playlist cover topics that can help you in your data science or ML journey.
Best way to learn mathematics and Statistics for data science and machine learning. This playlist cover topics that can help you in your data science or ML journey.
In this machine-learning tutorial in Hindi, we will explain machine learning to begin machine learning with python tutorial series of Codebasics. Explore more.
In this tutorial, you will learn sales insights data analysis project using power BI. This project will give you a feel of how data analysis projects are executed.
How do switch careers to data science? In this tutorial, you will learn how a person with different background can transition to different roles in data science.
This python object-oriented programming tutorial will explain “class” and “objects”. It has covered what a class is, how to create a class in python.
Unit Testing in Python: We will see python’s testing frameworks, how to install pytest using pip, unit test coding, and assert statements in unit tests and commands.
Free Jupyter Notebook Online Tutorial in Python: This tutorial explains what is Jupiter or ipython notebook. Learn more here.
In this time series analysis in pandas tutorial, we are going to start time series analysis tutorials with DatetimeIndex and Resample functionality. Learn more.
This Python numpy tutorial covers an introduction to the NumPy python module. We'll see why it is very popular and talk about its main feature n-dimensional array
Pandas in Python Tutorial: If you are working on data science, you must know about pandas python module. learn data science, functionality, and Installation of Pandas.
Learning knows no limits. Here’s to your journey of seamless
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& free resources.
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