Python Advanced Training

Python course helps you gain expertise in Quantitative Analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will use libraries like Pandas, Numpy, Matplotlib, Scikit and master the concepts like Python Machine Learning Algorithms such as Regression, Clustering, Decision Trees, Random Forest, Naïve Bayes and Q-Learning and Time Series.

Enrolment validity: Lifetime

About This Course

Our Python Certification Training not only focuses on the fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands-on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.

Below are the major features and applications due to which people choose Python as their first programming language:

  • Python’s popularity & high salary
  • Python is used in Data Science
  • Python’s scripting & automation
  • Python used with Big Data
  • Python supports Testing
  • Computer Graphics in Python
  • Python used in Artificial Intelligence
  • Python in Web Development
  • Python is portable & extensible
  • Python is simple & easy to learn

There are no specific prerequisites for taking up the Python Programming Certification Training. Basic understanding of Computer Programming terminologies is beneficial.

Learning Objectives

Programmatically download and analyze data
Learn techniques to deal with different types of data – ordinal, categorical, encoding
Learn data visualization
Using I python notebooks, master the art of presenting step by step data analysis
Gain insight into the ‘Roles’ played by a Machine Learning Engineer
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and its related concepts
Perform Text Mining and Sentimental analysis
Gain expertise to handle business in future, living the present

Target Audience

  • Programmers, Developers, Technical Leads, Architects
  • Developers aspiring to be a ‘Machine Learning Engineer’
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Machine Learning (ML) Techniques
  • Information Architects who want to gain expertise in Predictive Analytics
  • ‘Python’ professionals who want to design automatic predictive models


122 Lessons25h

Introduction to Python

Need for Programming
Overview of Python
Python Installation
Operands & Expressions
Conditional Statements
Command Line Arguments
Practical Exercise

Python Functions

Complex Data Types

Classes & Inheritance

Advanced Classes

Advanced Inheritance

Advanced functionality of Classes & Inheritance

File Operations in Python

Advanced Operations Using for Loops in Python

Modules & Virtual Environments

Exceptions & Command Line Arguments

Major Project



Duration 25 hours
122 lectures

Material Includes

  • 180 days Access
  • Self-Paced Learning
  • Downloadable Content - ebooks
  • Practical Exercises/Quizzes/Projects
  • Resume support
  • Linkedin profile optimization
  • Course Completion Certificate
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