Artificial Intelligence and machine Learning With Python Online Training Course:


$149 Price

Absolutely Free
Free study Materials

$328 Price

Advanced sessions
Interview Q&A
Free study Materials
Premium Technical support

Contact US

Advanced sessions
Interview Q&A
Free study Materials
Premium Technical support


Module 1
Installation of jupyter Notebook Setup with Python (AI Development

  • What Is Artificial Intelligence
  • Level Of product
  • Introduction Of Machine Learning
  • Types of Data Analytics
  • Introduction To Statistics
  • Application Of Machine Learning
  • Machine Learning Cloud Platforms
  • Objective Of Machine Learning Algorithm
  • Introduction of Deep Learning
  • Machine Learning VS Deep Learning
  • Application of Deep Learning.
  • Introduction to Data Science
  • Introduction to Data Analytics
  • Difference Between Data Science and Business Intelligence
  • Turing Test
  • History of Data Science
  • Important Scientists to follow in the field of Machine Learning
  • Why do we care about Data Science?

Module 2

  • Hands on practice on Python Programming Language
  • History Python 2 vs python 3
  • Data Types and Data Structure with Python
  • Methods and Functions in Python
  • Object Oriented Programming In python.
  • Python fundamentals and required libraries for the course
  • Functions from numpy, matplotlib, scikit-learn and various other libraries
  • Graph and Images in python
  • Data Analysis
  • Hands on practice with Salaries Dataset
  • Statistical Analysis
  • Data Visualization with Seaborn and Pyplot
  • Hands on Practice with Ariflight Dataset.

Module 3

Linear Regression

  • What Is Linear Regression?
  • Univariate Linear Regression
  • Hands on practice with Salary Dataset
  • Gradient Descent Algorithm
  • Linear Regression Use Cases
  • Objectives of Linear Regression
  • Multivariate Linear Regression
  • One Hot Encoding and Dummy Variable
  • Gradient Descent with Multiple Variable
  • Hands On practice with Startup Funding Dataset
  • Polynomial Regression
  • Hands On practice with 50 Startup Dataset
  • Linear Regression Assumptions

Module 4

Logistic Regression

  • What Is Logistic Regression?
  • Logistic Regression Features
  • Objective of Logistic Regression
  • Activation Functions:

1. Sigmoid Function
2. Softmax Function

  • Model Evaluation
  • Confusion Matrix

1. True Positive and True Negative
2. False Positive , False Negative
3. Accuracy, Precision
4. Recall, F1-Score

  • Over Fitting & Generalisation
  • Hands On practice with Bank Marketing Dataset
  • Hands On practice with Social Network Advertisement Dataset

Module 5

Decision Tree

  • Decision Tree Introduction
  • Classification Tree
  • ID3 Algorithm

1. Entropy
2. Information Gain

  • CART algorithm

1. Gini Index
2. Gini Impurity

  • C4.5 Algorithm
  • Chi-Square Algorithm
  • Regression Tree
  • CART Algorithm

1. Variance

  • Advantages and Disadvantages of Decision Tree
  • Hands on Practice of Decision Tree with Breast Cancer Dataset

Hands on Practice of Decision Tree with Social Network Advertise Dataset
Using the Decision Tree Algorithm for analysing a real-life dataset
Module 6
Random Forest

  • What is Bagging?
  • How Random Forest Algorithm is a very major upgrade from Decision Tree?
  • How does Random Forest handle Missing Data?
  • Random Forest as Classifier
  • Random Forest as Regressor.
  • Random Forest Algorithm using SciKit Learn Library. Calculation of Accuracy and F1 Score
  • Comparing Results of Decision Tree and Random Forest Algorithms for
  • Breast-Cancer Dataset.

Module 7
Artificial Neural Network

  • What is an Artificial Neural Network?
  • Introduction to Neurons
  • Single Neuron Model
  • Activations Functions:

1. Sigmoid
2. Softmax
3. Relu
4. Leaky Relu Functions

  • Neural Network Architecture
  • Types of Neural Network
  • Application, Advantages and Limitations
  • Hands on practice of Artificial Neural Network with Churn Modelling Dataset.

Module 8
Support Vector Machines

  • What are Convex Hulls?
  • What is a hyperplane?
  • What is weight and bias?
  • Why is SVM is one of the best classification algorithms till date?
  • Support Vector Machine Algorithm Derivation.
  • A discussion on techniques to apply support vector classification on linearly
  • inseparable datasets. (using Kernels or increasing the dimensionality of the dataset)

Do you like the curriculum?


Demos at Convenient Time?
1-1 Training
Batch Start Dates At your Convenience Fixed
Customize Course Content
LifeLong Access to LMS
24*7 Support
EMI Option
Group Discounts


Do you have any Queries?


We the Meritstep are an online learning platform. The cyber training of Meritstep comes in various f
We are a group of people, who are experts in the IT field, and holds in-depth knowledge in the corpo
Anytime from anywhere, you can do our courses. Meritstep provides complete online courses, as we hav
We have people like the high time corporate professionals with years of experience and educated in t
Our courses are 24*7 accessible. There is really least chance of missing any class. Although if you
Meritstep courses are such way designed that students become experts over real-time works while they
If you are already enrolled in classes and fees payment is done, and then the cancellation decision
Yes. The Meritstep training is Real-time Project Oriented, which makes our students highly skilled.
Yes. We provide some group Group discounts available if the participants are more than 2.
As we are one of the leading providers of Live Instructor LED training. And our online course module
Meritstep only brings you such courses which are considered as the hotcake skills in the market. By
In every step of your learning Meritstep team and the trainers assist you with your subjective quest
Right now. You can enrol anytime you want. But being a skill development company, we suggest our asp

Have More Questions. Reach our Support Team

Customer Success Stories

Request a Free Demo

Call us on : +911234567890