Complete Data Science Training with Python for Data Analysis

Complete Data Science Training with Python for Data Analysis

Complete Data Science Training with Python for Data Analysis. Beginners python data analytics : Data science introduction : Learn data science : Python data analysis methods tutorial

Complete Guide to Practical Data Science with Python: Learn Statistics, Visualization, Machine Learning & More

It’s A Full 12-Hour Python Data Science BootCamp To Help You Learn Statistical Modelling, Data Visualization, Machine Learning & Basic Deep Learning In Python!

First of all, this course a complete guide to practical data science using Python…

That means, this course covers ALL the aspects of practical data science and if you take this course alone, you can do away with taking other courses or buying books on Python-based data science.

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By storing, filtering, managing, and manipulating data in Python, you can give your company a competitive edge & boost your career to the next level!

Complete Data Science Training with Python for Data Analysis Description

Requirements

  • Be Able To Use PC At A Beginner Level, Including Being Able To Install Programs
  • A Desire To Learn Data Science
  • Prior Knowledge Of Python Will Be Useful But NOT Necessary

Build Library Management System – Python & PyQt5 Course

What you’ll learn

  • Python data analytics – Install Anaconda & Work Within The iPytjhon/Jupyter Environment, A Powerful Framework For Data Science Analysis
  • Python Data Science – Become Proficient In Using The Most Common Python Data Science Packages Including Numpy, Pandas, Scikit & Matplotlib
  • Data analysis techniques – Be Able To Read In Data From Different Sources (Including Webpage Data) & Clean The Data
  • Data analytics – Carry Out Data Exploratory & Pre-processing Tasks Such As Tabulation, Pivoting & Data Summarizing In Python
  • Become Proficient In Working With Real Life Data Collected From Different Sources
  • Carry Out Data Visualization & Understand Which Techniques To Apply When
  • Carry Out The Most Common Statistical Data Analysis Techniques In Python Including T-Tests & Linear Regression
  • Understand The Difference Between Machine Learning & Statistical Data Analysis
  • Implement Different Unsupervised Learning Techniques On Real Life Data
  • Implement Supervised Learning (Both In The Form Of Classification & Regression) Techniques On Real Data
  • Evaluate The Accuracy & Generality Of Machine Learning Models
  • Build Basic Neural Networks & Deep Learning Algorithms
  • Use The Powerful H2o Framework For Implementing Deep Neural Networks

Who this course is for:

  • Anyone Who Wishes To Learn Practical Data Science Using Python
  • Anyone Interested In Learning How To Implement Machine Learning Algorithms Using Python
  • People Looking To Get Started In Deep Learning Using Python
  • People Looking To Work With Real Life Data In Python
  • Anyone With A Prior Knowledge Of Python Looking To Branch Out Into Data Analysis
  • Anyone Looking To Become Proficient In Exploratory Data Analysis, Statistical Modelling & Visualizations Using iPython

Complete Data Science Training with Python for Data Analysis Free Download

Google Drive (Public)

Content From: https://www.udemy.com/course/complete-data-science-training-with-python-for-data-analysis/

Give a Comment