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Data Science Diploma: Machine Learning with Python

  • Level up your data analytics skills by learning how to apply various data science and machine learning techniques to analyze and visualize a data set using Python.
  • Upon completion of this course, you'll be able to write your own Python scripts and perform data analysis using Python language.
  • You will learn Python from scratch and practice through lab exercises and hands-on methods.
  • Processing and managing your data in Python, discover the patterns and draw predictions that would enable you to give your company a competitive edge and also help you to boost your career to the next level.
  • High Demand: Data Science was chosen as the #1 career in 2019 as the fastest-growing job.
  • High Paying Jobs: Data Scientist is one of the highest paying jobs.
  • Easy to learn: Python has few keywords, easy structure, and a clearly described
  • Easy to read: Python code is more virtually described and visible to users.
  • Easy to maintain: Python's source code is fairly easy to preserve.
  • A broad standard library: Python's library is cross-platform compatible on Windows and Macintosh.
  • Interactive Mode: Python allows interactive checking out of snippets of code.
  • Portable: Python can run on a vast range of hardware structures and has an equal interface on all platforms.
  • Databases: Python offers interfaces to all fundamental business
  • Scalable: Python affords a better structure and support for large applications than shell scripting.
  • Accessible: Python is a free, flexible and powerful open source language
  • Needs to learn practical data analytics using Python.
  • Needs to start his / her career in the field of data science.
  • Needs to enhance his / her analytical skills.
  • Needs to implement Machine Learning algorithms using Python.

Diploma Objectives:

In this training program, you will learn how to collect, process, analyze and visualize any size of data to get the conclusions supporting you taking the right decision for your business and build a data models to help you find the predictions to plan for the future.

  • Learn all Python basics.
  • Learn OOP (Object-Oriented Programming) and data structures in python.
  • Learn The important topics in data science and mathematics.
  • Learn the most needed data science algorithms.
  • Be able to deal with all files using python.
  • Be able to implement any algorithm or program using python after the first six sessions; even without GUI (Graphical User Interface).

Diploma Topic: [Python Part]

  • Introduction
  1. What‘s Data Analysis?
  2. What‘s Data science? Trends? Artificial Intelligence ‘AI’? Machine Learning?
  3. What’s the Difference between Excel Data Analysis and Programming?
  4. Why Python?
  5. Different fields python can fit.
  6. Different Python versions.
  7. Environment setup.
  • Basics
    1. Basic Syntax.
    2. Data Types.
    3. Operators.
    4. Decisions.
    5. Loops.
    6. Strings.
    7. Functions.
    8. Most needed library and tools.
  • OOP (Object-Oriented Programming)
    1. Classes
    2. Objects
    3. Data members
    4. Overloading
    5. Inheritance
  • Data Structures
    1. List and tuples
    2. Sets
    3. Dictionaries
  • Files and Databases
    1. Reading from Files
    2. Writing into files
    3. Database Connections
    4. Dealing with files using pandas
  • Advanced Topics
    1. Multi threads
    2. Sockets
    3. APIs

Diploma Topic: [Data Science part]


  1. Introduction to data science                
    • Data science trends?
    • Statistics Refreshment (Descriptive and Inferential)
    • Mathematics Refreshment
  2. Supervised Learning
    • Linear Regression
    • Logistic Regression
  3. Unsupervised Learning
    • Clustering
  4. Machine Learning
    • What‘s Machine Learning?
    • What’s Deep Learning?
    • Neural Networks:
      • Neural Network Architecture and How it works
      • Neural Network Implementing
    • Intro to Tensor Flow
  5. Data Visualization
  6. Recommended Systems
  7. Full Business Case


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