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Python for Data Science

Course Summary

Python is the most popular programming language for data science as on today. Python is powerful, easy to learn and flexible tool for coding data science and machine learning algorithms. In recent years, python has evolved immensely with respect to data science sphere, with a huge community around python creating quite a few power data science and analytics packages such as Pandas, Numpy, Scikit Learn, Scipy and more. As a result, analyzing data, modeling machine learning algorithms with python has never been easier.

This course is designed for candidates with or without programming skills, with basics of data importing, data mugging and coding machine learning algorithms along with effective programming techniques. This also includes python data science challenges kit, enabling the candidates to not only understand python core concepts but also gain practical mastery over python for data science, which is very much in demand in today's data science job opportunities.


Course Objectives

The objective of this course is to provide the fundamentals of Python programming and introduce Data Science concepts and Machine Learning.

  • Python Fundamentals : Understanding Python syntax, data types, operators, conditional statements, functions. Writing simple Python scripts for Data Science
  • Data Science essentials: Understand the core concepts of Data Science. Data exploration, data mugging, data pre-processing and transforming data for further analysis. Gain familiarity with Python packages Numpy and Pandas
  • Python for Machine Learning(ML): Understand core concepts of Machine Learning and practice simple ML algorithms using Python package Scikit Learn

Course Outline

Python programming fundamentals

  • Programming Basics
  • Python Data Types
  • Structures and conditional statements
  • Python core packages
  • Introduction to Jupyter Notebook

Data science essentials

  • Data Science Introduction
  • Data Science work flow
  • Machine Learning Overview

Data mugging with numpy and pandas

  • Introduction to Numpy and Pandas
  • Data filtering and selecting
  • Find duplicates and treating missing values
  • Concatenate and transform data

Basic statistics

  • Basic Statistics and Exploratory Analysis
  • Descriptive summary statistics with Numpy
  • Summarize continous and categorical data
  • Outlier analysis

Visualization, web scraping

  • Creating basic charts
  • Statistical Charts
  • Web Scrapping tools

Introduction to machine learning

  • Overview of Supervised and Unsupervised Machine Learning
  • Linear Regression
  • Clustering with K-means
  • Naive Bayes Classification
  • Introduction to Neural Networks

Who can benefit from this course?

Any professional aspiring to become a data scientist can start from this course.

  • Candidates wanted to pursue Data Science career, with basic or no programming skills
  • Seasoned conventional programmer aiming to gain basic machine learning coding skills
  • Job seekers, pursuing a career as Data Science Developer
  • Professionals, whose job involves Data Science and Python

Prerequisite

This course is a beginner level, so most Data Science aspirants can opt for Python for Data Science

  • Basic Programming is recommended
  • Basic Statistics knowledge is recommended

Course Objectives

The objective of this course is to provide the fundamentals of Python programming and introduce Data Science concepts and Machine Learning.

  • Python Fundamentals : Understanding Python syntax, data types, operators, conditional statements, functions. Writing simple Python scripts for Data Science
  • Data Science essentials: Understand the core concepts of Data Science. Data exploration, data mugging, data pre-processing and transforming data for further analysis. Gain familiarity with Python packages Numpy and Pandas
  • Python for Machine Learning(ML): Understand core concepts of Machine Learning and practice simple ML algorithms using Python package Scikit Learn

Course Outline

Python programming fundamentals

  • Programming Basics
  • Python Data Types
  • Structures and conditional statements
  • Python core packages
  • Introduction to Jupyter Notebook

Data science essentials

  • Data Science Introduction
  • Data Science work flow
  • Machine Learning Overview

Data mugging with numpy and pandas

  • Introduction to Numpy and Pandas
  • Data filtering and selecting
  • Find duplicates and treating missing values
  • Concatenate and transform data

Basic statistics

  • Basic Statistics and Exploratory Analysis
  • Descriptive summary statistics with Numpy
  • Summarize continous and categorical data
  • Outlier analysis

Visualization, web scraping

  • Creating basic charts
  • Statistical Charts
  • Web Scrapping tools

Introduction to machine learning

  • Overview of Supervised and Unsupervised Machine Learning
  • Linear Regression
  • Clustering with K-means
  • Naive Bayes Classification
  • Introduction to Neural Networks

Who can benefit from this course?

Any professional aspiring to become a data scientist can start from this course.

  • Candidates wanted to pursue Data Science career, with basic or no programming skills
  • Seasoned conventional programmer aiming to gain basic machine learning coding skills
  • Job seekers, pursuing a career as Data Science Developer
  • Professionals, whose job involves Data Science and Python

Prerequisite

This course is a beginner level, so most Data Science aspirants can opt for Python for Data Science

  • Basic Programming is recommended
  • Basic Statistics knowledge is recommended

Contact Us

We moved to below new address! Suite 610 - The Business Center, Opp to Burjuman Centre, Adjacent to Burjuman Metro Station Exit 4, Khalid Bin Walid Street. P.O.Box: 94743 Dubai, UAE.

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