×

This course is for the intermediate to Advance level participants. The participants should know the basic Python programming language. Prior familiarity with some other programming language (such as Java or C++) would be useful, but it is not mandatory for the audience.

After completing this Machine Learning Certification Training using Python, you should be able to:

  • In-depth knowledge of of Python
  • In-depth knowledge of Data Science
  • In-depth knowledge of Machine Learning
  • Work with real-time data
  • Learn data visualization
  • Learn tools and techniques for predictive modeling
  • Discuss Machine Learning algorithms and their implementation
  • Gain expertise to handle business in future, living the present
Topics Name
Online Session
Online Session
Control Structure

undefined

Functions

undefined

Built in Functions

undefined

Dictionary Case Study

undefined

List Comprehension and Dictionary Comprehension

undefined

Module

undefined

Built In Modules

undefined

File Handling and Exception Handling

undefined

OOPS Application

undefined

Inheritance, Polymorphism, Overloading and Overriding

undefined

Iterator, Generator and Collection Framework

undefined

Introduction to Data Science

undefined

Data Processing

undefined

Mathematical Computing with NumPy

undefined

Data Manipulation with Pandas

undefined

Data Visualization using matplotlib

undefined

Introduction to Python

Python Introduction, Applications of Python

Object Oriented Programming using Python

undefined

Regular Expression: With Case Study

undefined

Introduction to Machine Learning

undefined

Supervised learning

undefined

Unsupervised learning

undefined

Reinforcement learning

undefined

Scikit-learn , Linear regression

undefined

Linear Regression case study

undefined

Introduction to Deep Learning and Neural Networks

undefined

Convolutional Neural Networks , Sequence Models

undefined

Improving and Optimizing a Neural Network

undefined

Natural Language Processing in TensorFlow

undefined

Building deep learning models with keras, Fine-tuning keras models

undefined

Data Structure

Primitive Data Structures, Non-Primitive Data Structures

Lab Setup:-

Computer with the following software

Operating System: Red Hat Linux / Ubuntu/CentOS/ Windows ( Latest Version preferable )

Anaconda python 3.7 ( Latest Version preferable )

https://www.anaconda.com/download

Python 3.7 version *

Set Up Python Path Environment on OS ( During Installation ). [ Shortest Path ]

Internet Access will be needed to install python third party library

 

Hardware :

RAM: Minimum 4GB / 8GB ( Recommended ).

Internet Connectivity. ( Needed to Install Packages and Run Anaconda Server ).

80 GB HDD.

Latest Course

R Programming
Trending Courses
PySpark
Trending Courses
Ruby on Rails
Snow
ChatBot

Hello! How can I help you?