Price  20,000.00  18,000.00

Course Features
Language: English
35 Hours of Training
Study Level: Advanced
Certificate of Completion


Machine learning training

Machine Learning with Python Course

  • 23rd Feb 2019 (5 Weekends) | Sat-Sun Training Mode: Online | 02:00 PM – 05:00 PM IST
  • 23rd March 2019 (5 Weekends) | Sat-Sun Training Mode: Online | 02:00 PM – 05:00 PM IST

Machine Learning With Python Course

Machine learning with python course is designed to focus on the basics of machine learning with the help of an approachable and a well known or common programing language. This course would help you understand the purpose of machine learning and how it is applicable in the real world. Also, this course would present with a general overview and understanding of most of the machine learning topics like; unsupervised vs supervised learning, machine learning algorithms as well as model evaluation. Also, this course would offer you real-life examples of how machine learning is applied. It will also teach you how machine learning affects the society in ways that most people would refer to as “impossible”. Asides these, you would also be taught about several courses that relate to machine learning. This course would also offer you the needed skills to help develop algorithms.

Machine Learning Certification Course

Main Features

  • Intensive instructor-led training and supervision
  • Would help you gain knowledge with detailed hands-on exercise
  • Would offer a practical application of over fifteen (15) machine learning algorithms.
  • Would help you understand and master the general concepts of unsupervised and supervised learning.

Learning Objectives

For Individuals
  •  Machine Learnig course would offer them extensive access to self-paced learning, designs, and contents that have been specially designed by experts in the machine learning industry.
For Businesses
  • Would offer them complete training solutions as well as well blended delivery models
  • Would offer regular and proper teaching, assistance and supervision
  • Would offer advanced reports for teams and individuals as well
Machine Learning with Python Course

Machine Learning with Python Course Description

With the growth of the industry and the real benefits of machine learning, it has become relevant that people learn about it. The increase of this industry would require professionals who would be able to understand the workings of the industry.

After you must have completed the course, you would have;

  • Mastered the concept of the industry
  • Understand the Python programming language
  • Would be capable of modeling or creating various machine learning algorithms.
  • This course was designed primarily for those that are passionate about the data science field.

Machine Learning with Python Curriculum

1. Introduction

1.1 Introduction to Data Science


Key Elements of Data Science
Data Warehousing
Business Intelligence
Data Visualization
Data Mining
Machine Learning
Artificial Intelligence
Cloud Computing
Big Data

1.2 Artificial Intelligence: A preview


What is Artificial Intelligence & its importance
Artificial Intelligence vs Machine Learning

2. Getting Started with Machine Learning

2.1 Overview of Machine Learnin

Quick tour of the types of machine learning


What is Machine Learning (ML)?
How machines learn
Types of learning: Supervised, Semi-supervised, Unsupervised, Reinforcement.
Basics of Classification, Regression and Clustering algorithms
Creating your first Prediction Model
Training & Model evaluation
Choosing Machine Learning algorithm

3. Back to Basics (Maths with Statistics)

3.1 A quick refresh on basic intermediate maths:


A quick refresh on basic intermediate maths:

Linear Algebra (Vectors, Matrix, Eigen Values)
Probability and Statistics
Hypothesis testing

4. Getting Started with Python

4.1 A quick crash course on basics of Python


A quick crash course on basics of Python

What is Python
Working with Python
Basic scripts on
Read, write, data handling
Conditions (if-else)
Code modularization
Scikit-Learn package
Basic visualization

5. Data Processing for Machine Learning

5.1 Introduction to Data Processing


Data Collection & Preparation
Data Mugging
Outlier Analysis
Missing value treatment
Feature Engineering
Data Transformation
Normalization vs Standardization
Creating Dummies
Dimensionality Reduction
Principal Component Analysis

6. Advanced Machine Learning Algorithm

6.1 Overview to Machine Learning Algorithms


Supervised Machine Learning algorithms
Linear Regression
Logistic Regression
Decision/Classification Tree
Ensemble Models
Random Forest
K-Nearest Neighbours (KNN)
Naive Bayes
Neural Network (Deep Learning)
Support Vector Machine
Unsupervised Machine Learning algorithms
Clustering with K-means Clustering
Bias-Variance Trade off
Parameter tuning & grid search optimization


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  • Kiran Kumar
    Rated 5 out of 5

    It is a great course, highly recommended for those who wants to work in AI / Data Science field or get a better understanding chance of these fast developing and highly sought after skills.

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