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Python Beyond Basics for Machine Learning, Data Science, AI
Rating: 4.5 out of 5(59 ratings)
575 students

Python Beyond Basics for Machine Learning, Data Science, AI

Data Science, Machine Learning and Artificial Intelligence with Python
Created byPiyush Dave
Last updated 9/2023
English

What you'll learn

  • Coding using one important Programming Language
  • Problem Solving Approach
  • Learn Python form Scratch
  • Learn Python from experienced professional Trainer
  • Understand complex functions of Python

Course content

15 sections102 lectures14h 0m total length
  • Course Introduction in Animation2:02
  • Why to join this course?1:32

    Join this course to learn basics quickly from a decade-experienced trainer, with 100 percent hands-on training and support files, notes, and an e-book, no prior knowledge required.

  • Introduction of Python and Python Libraries7:58

    # Intro of python and python libraries:

    Python is an example of high-level language. Programs written in high level language have to be processed before they can run. It takes less time to write, they are shorter and easier to read, and they are more likely to be correct. They are portable means they can be run on different kinds of computers with few or no modifications. A python library is a reusable chunk of code that you may want to include in your programs or projects. Libraries basically describes collection of modules.

  • Meet Trainer for this Course1:17

    Jenny introduces Trayner for this Python beyond basics course, notes the expert trainer lineup, invites questions in the Q&A, and explains five-star ratings after watching two to three videos.

  • Data Science Introduction10:16

    Explore the introduction to data science through a practical case study, analyzing customer satisfaction and loyalty with data analytics to boost business strategy.

Requirements

  • It start with Basics
  • Only Basic Mathematics Concept
  • This course is intended for absolute beginners in programming

Description

Learn the Most demanding language of industry with concept applied to Data Science, Machine Learning and AI

Important topics  are covered such as Python Basic Concepts, Advance Concept, Python Crash Course, Python Libraries such as numpy, pandas, matplotlib, seaborn, Data Science Concept with Case Studies , Machine Learning and it's types, Artificial Intelligence with Case Studies

This Course will design to understand Data Visualization and Data Analysis with  Machine Learning Algorithms with case Studies. 

Data Analysis with Machine Learning Algorithms  such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered.

The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered.

Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.

The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered.

Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.

Data Visualization and Analysis with ML using Python, Numpy Pandas, Matplotlib, Seaborn, Plotly & Scikit Learn library

This Course will design to understand Machine Learning Algorithms with case Studies using Scikit Learn Library. The Machine Learning Algorithms  such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered with case studies

Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.


Who this course is for:

  • Learner who wants to work as python developers
  • People interested to learn how to program in python
  • Learner who wants to start career as Python Developer, Data Science and AI