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Python with Data Science & Machine Learning

This Course is the most comprehensive ML course with a scope of learning Data Analytics, Data Visualisation along Core concepts of Python. It aims to acquaint the student with all the Parts consist of the course on Data Analytics, Data Visualisation concepts, Machine learning along with a fair amount of exposure on projects and exercises.

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Why should you take Python?

There has been a 256 percent increase in Data Science since 2013, which suggests companies recognize the worth of data scientists and want to add them to their teams.

Data Science named "the most promising career in 2019" by LinkedIn and the "best job in America" by Glassdoor, it’s not just the earning power. The money is great, with a median base salary of $108,000,

According to Glassdoor, data scientist also tops the charts based on job satisfaction. And, according to LinkedIn, the career path readily leads to promotions.

Classroom Training/Instructor led Python Live Online Classes

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Course Syllabus

PART -1 Python

The print statement


Basic data types introduction

String Operations in Python

Simple Input & Output

Simple Output Formatting




List Method




Frozen sets

Mutability and immutability

Type Casting


The If statement and its’ related statement

An example with if and it’s a related statement

The while loop

The for loop

The range statement

Break & Continue statements

Enumerate, zip & tuple unpacking

Examples for looping

Create your own functions

Functions Parameters

Variable Arguments

Scope of a Function

Function Documentation/Docstrings

Lambda Functions

Map and Filter

Exercise with functions

  • Errors
  • Exception Handling with try
  • Handling Multiple Exceptions
  • Writing your own Exceptions

File Handling Modes

Reading Files

Writing & Appending to Files

Handling File Exceptions

The with statement

Classes introduction

Variable Type

Creating Classes

Defining objects

Instance Methods



Simple Character Matches


Special Sequences

Regex sets

Matching at Beginning or End

Match Objects


Splitting a String

Introduction to MongoDB


DB Connection with Python

Creating DB collections

Insert, Read, Update, Delete operations

Part -2 Data Anlytics and Data Visulization

Introduction to Numpy

Creating and Printing an array

Indexing and slicing of an array

Numpy Operations

Numpy Methods

Numpy Exercise

Numpy Exercise Solutions

Introduction of Pandas

Understanding Series

Series Operations

Understanding DataFrame

View and Select Data Demo

Missing Values



File Read and Write Support

Projects 1 Using Pandas (Getting insights from salary dataset)
Projects 2 As assignment (on Ecommerce Purchase Dataset)

Introduction to Matplotlib

Matplotlib Part 1

Matplotlib Part 2

Seaborn introduction

Distribution & categorical plots using seaborn

Heatmap using Seaborn

Plotly introduction

Geographical plotting


Part -3 Machine Learning

Introduction to SVM

Working with High Dimensional Data

Working of SVM and its uses

Breast Cancer Prediction Project using SVM

Need for dimensionality reduction

Principal Component Analysis (PCA)

PCA with Python on cancer Dataset

Conditional Probability

Overview of Naïve Bayes Algorithm

News Classification Project using naïve Bayes classifier

Basic of Computer Vision & OpenCV

Images Manipulations

Image Segmentation

Object Detection

Face, People and Car Detection

Machine Learning in Computer Vision

Motion Detection Project using Opencv

Introduction to neural networks

Perceptron model

Activation functions in NN

Introduction to Tensorflow

MNIST project Overview
MNIST project Solution
Fashion MNIST Project

NLP introduction

NLP with Python Part 1 (bag of words)

NLP with Python Part 2 (TF-IDF)

Spam-Ham message detection NLP Project

Introduction to Machine Learning

Understanding supervised and unsupervised learning with examples

Test-train split

Underfitting and overfitting

Linear Regression Theory

Dependent and independent Variables

Linear Regression with Python

Linear Regression Project on Predicting House Price

Logistic Regression Theory – Introduction

Logistic Regression with Python – Part 1 – EDA

Logistic Regression with Python – Part 2 – ML Model

Logistic Regression with Python – Part 3 – Conclusion

Logistic Regression Project on Titanic Dataset Overview and Project Solutions

KNN Theory

KNN with Python

KNN Project Overview and Project Solutions

K Means Algorithm Theory

K Means with Python

K Means Project Overview

K Means Project Solutions

Introduction to decision trees

Entropy and Information gain

Introduction to bagging algorithm

Random Forests

Project on tree models
Project solution

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The constructs of this Python Language make it easier for a non-technical person to understand and grab it . Python is is definitely one of the easiest programming languages to learn. This is infact the best first language to learn. Even the learners from a non-technical background will start liking the language after a while.

Today, while Python becoming the de facto industry standard in financial analysis, e-commerce, retail business, many found the jobs required it as a core competency and charted a learning path with us while learning in classroom or online mode. Students at our institute comes from varied background and learn to not only code fluently but build solutions finding them a space in analytics companies as data analysts. Many have turned to be full-stack developers and business analysts.

Yes, All our courses at Python Training institute are available on both Weekdays as well as on Weekends mode. Infact most of our courses are available in Online mode as well.

There are usually 7-8 students in a batch.

Although you will get an Autonomous certificate from Python Training institute, and additionally students will also get a certification from Microsoft after passing out the exam successfully.

All our courses comes with Projects and Assignments at various stages of the course curriculum. You can refer the course syllabus for the same.

Yes, at Python Training institute we are pleased to offer you one Demo and Trial Class for better understanding about course flow, teaching style of trainer and to get acquainted with learning atmosphere.

You can give us a CALL at 18001020418 (Tollfree Number) OR email at info@pythontraining.com

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Aditya Prakash

Amazing classes, great staff and wonderful lectures, all who are interested in learning python should have no confusion but just come here.
- Aditya Prakash


Python Course at Python Training (TGC) south ex. was completed on time. I am fully satisfied with the quality of education provided by our teacher Uttam Saxena and the infrastructure provided by the institute
- Tanmay


“I enrolled for Python and very much satisfied with the training program, I will give Python Training Institute the highest number. My first thank goes to my SIR whom I’m pressed the most. My best wishes for the center.”
- Siddhant

Rupam Dubey

It was a great experience learning python from a trainer who is very friendly and gives an opportunity to every trainee to learn and enjoy the session. The course was completed with best examples that could be provided. Thank You.
- Rupam Dubey

Akansha Rai Sharma

The best training institute in Delhi for python. faculty you can count on. awesome management and staff.
- Akansha Rai Sharma


I wanted to thank everyone for helping me a lot. Before I started a course, I was not confident in myself. From the beginning of the course, they have shown great professionalism, patience, and encouragement. They helped me a lot on my first job. They showed me a great path.
- Aakash

Approvi Mittal

I think the Python classes very well structured in terms of the content that was going to be taught every class. hats off to Uttam Saxena sir. He was very patient – especially since I had no experience with programming and it was my first time. Hoping to come back to learn more course was completed.
- Approvi Mittal

Manjeet Kaur

I got good and sufficient knowledge from Python Training Institute in python. Also, training environment was very good.Best training institute ever.
- Manjeet Kaur
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