|Course or Certification Name||Category||Location||Mode of learning|
|The Complete Python 3 Course: Beginner to Advanced!||Data Science||Online self study|
|Vskills Certified Python Developer Government Certification||Emerging Web Technologies||Offline self study|
|XLRI Executive Program in Data Science using Python, R & Excel||Data Science||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|AI Programming with Python||Machine Learning||Online self study|
|Machine Learning with Python Training||Machine Learning||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Data Science And Analysis: Make DataFrames in Pandas And Python||Data Science||Online self study|
|Data Visualization with Python: The Complete Guide||Data Visualization||Online self study|
|Clustering & Classification With Machine Learning in Python||Machine Learning||Online self study|
|Python Programming An Expert Guide on Python||Emerging Web Technologies||Online self study|
|Python Programming Learn Python with 100+ Practicals||Emerging Web Technologies||Online self study|
|Applied Data Science with Python Specialization||Data Science||Online self study|
|DATA SCIENCE WITH R, PYTHON & MACHINE LEARNING||Data Science||Classroom|
|Introduction to Python Programming||Web Technologies||Online self study|
|Programming for Data Science with Python||Data Science||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Hands-On Image Recognition: Python Data Science Bootcamp||Data Science||Online self study|
This program evaluates aspirants on developing applications based on Python language. Python Development certification checks professionals on several fields of developing i.e. Python based software development encompassing installation awareness, usage, syntax and semantics of the language. It is required to have fundamental awareness about Object Oriented Programming Principles as a pre requisite for this course.
Businesses today are trying to engage with data science in one form or another. Unfortunately, only a few have been able to even grasp the idea of what constitutes data science, let alone implement it usefully and profitably. This program introduces its participants to the world of data science. The objective is to strip away all the distractions around data science – codes, tools, etc., and teach the techniques using practical cases that can be understood and appreciated by someone with an elementary knowledge of mathematics. This program uses hands-on approach to data science where participants get to work with data sets to generate insights for businesses. | The objective of this program is to introduce participants to the world of data science. The purpose of this program is to strip away all the distractions around data science – codes, tools, etc., and teach the techniques using practical cases that can be understood and appreciated by someone with an elementary knowledge of mathematics.
Learn the essential foundations of AI: the programming tools (Python, NumPy, PyTorch), the math (calculus and linear algebra), and the key techniques of neural networks (gradient descent and backpropagation).
Machine Learning with Python course discusses concepts of the Python language such as file operations, sequences, object-oriented concepts, etc. along with some of the most commonly leveraged Python libraries like Numpy, Pandas, Matplotlib, etc. The course will then move on to introduce learners to the detailed mechanisms of Machine Learning. Learners will understand in detail the significance of the implementation of Machine Learning in the Python programming language, and leverage this knowledge in their role as data scientists. | After completing the course, one would have learnt about tools to train machines based on real-world situations using Machine Learning algorithms, as well as to create complex algorithms based on concepts related to deep learning and neural networks. During the latter stage of the course, learners will be introduced to real-world use cases of Machine Learning with Python for a holistic learning experience which would prepare them to create applications efficiently.
This course is suitable for coding beginners because we begin with a complete introduction to coding. Then we delve deep into using pandas, an open source library with high-performance and easy-to-use data structures and data analysis tools written for Python.
The course will start at the very beginning helping you understand the importance of Data Science, along with becoming familiar with Matplotlib, Python’s very own visualization library. From there you will learn about the linear general statistics and data analysis. That’s not all, we’ll also cover important concepts such as data clustering, hypothesis gradient descent and advanced data visualizations. At the end of this course, you’ll have a working knowledge of data visualization using Python and you’ll also be able to build your own visualizations from scratch.
This course covers main aspect of practical data science and if you take this course, you can do away with taking other courses or buying books on Python based data science.This course will give you a robust grounding in the main aspects of machine learning- clustering & classification.
In this tutorial, you will be introduced to Python Version 3.x. You will learn the basic syntax using a hands-on approach. This guideline will not only familiarize you with the basics, but also it will demonstrate the Python IDE (Integrated Development Environment), for writing actual programs and learning how to debug them.
In this course, we have designed a detailed course to become your guide. You will learn the techniques and concepts of Python programming, giving you the information and the skills you need to boost your programming skills and learn Python.
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
Machine learning is one of the key components of datascience. R and Python are one of the most used programming languages and command a huge demand in the data science job market. This module gives you exposure to both R and Python that prepares you for delivering in either of the platforms.
In this course, you'll learn the fundamentals of the Python programming language, along with programming best practices. You’ll learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs. You’ll harness the power of complex data structures like lists, sets, dictionaries, and tuples to store collections of related data. You’ll define and document your own custom functions, write scripts, and handle errors. Lastly, you’ll learn to find and use modules in the Python Standard Library and other third-party libraries.
Prepare for a data science career by learning the fundamental data programming tools: Python, SQL, command line, and git. By the end of the program, you will be able to use Python, SQL, Command Line, and Git.