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Are you Looking for the Best Institute for Data Science using Python training in Noida? DUCAT offers Data Science using Python training classes with live project by expert trainer in Noida. Our Data Science using Python training program in Noida is specially designed for Under-Graduates (UG), Graduates, working professional and also for Freelancers. We provide end to end learning on Data Science using Python Domain with deeper dives for creating a winning career for every profile.

Why To Enroll In Our Data Science using Python Training Course in Noida?

We Focus on Innovative ideas, High-quality Training, Smart Classes, 100% job assistance, Opening the doors of opportunities. Our Data Science using Python Trainees are working across the nation. We at Ducat India, No#1 Data Science using Python Course in Noida with 100% Placement. Certified Trainers with Over 10,000 Students Trained in Data Science using Python Course in Noida.

What Our Students Will Get During Data Science using Python Training Course?

Get dedicated student support, career services, industry expert mentors and real world projects. Career Counselling. Timely Doubt Resolution. 50% Salary Hike, Career Counselling Case Studies + Tools + Certificate.

Python language is an open-source language that is used to simplify and easily access the data and store the data. Data Science using Python Training in Noida program is intended to help you learn the fundamentals and basics of Python language and its eco-system. The student will be learning to learn basic syntax and variables as well as types to build the foundation. Students will be introduced to the different techniques used for creating, cleaning and manipulating Python lists in the course. The course will cover the learning of functions, import packages, and Panda Data Frames. The student will also learn how to build numpy arrays and how to use them for complex calculations. During the entire training program, candidate will: Know the differences between 2.X and 3.X, Create compelling graphics to reveal analytic results, Learn the difference between Python basic data types, Reshape and merge data to prepare for advanced analytics, Find test for group differences using inferential statistics, Understand to implement python functions, Learn control flow constructs in Python, Know when to use different python collections, Handle errors through handling constructs, Understand non-linear terms, confounding, and interaction in linear regression, Know to define an answerable, actionable question, Import both structured and unstructured data into Python, Extend logistic regression to model binary outcomes, Implement cataloging and regression models using machine learning.

Why learn Data Science using Python?

It's continued to be a great option for data scientists who use it for building Machine learning applications or and using them and other scientific computations. Data Analytics Using Python Training in Noida cuts development time in half with its simple to read syntax and easy compilation feature with easy to learn the concept. Debugging any type of programs is a breeze in this language with its built-in debugger. It runs on every famous type of platforms like Windows, Linux/Unix, and Mac OS and has been ported to Java and .NET virtual machines. Python is free to use language, even for commercial products, because of its OSI-approved open source license, so anyone can use it for free. It has opted as the most preferred Language for Data Analytics and the increasing search trends on Python every day also indicates that it is the "Next Big Thing" and a must for aspirants in the Data Analytics field.

This Data Science using Python Training not only focuses on basics of Python, Machine Learning and Spark but it will also helps anyone gain expertise on applied Data Science using Python. The training course is a step by step guide to Python and Data Science with extensive training with live projects. This course will also cover both basic and advanced concepts like writing Python scripts, sequence and file operations in Python. You will be using libraries like pandas, matplotlib, scikit and will master the concepts like machine learning, scripts, sequence, web scraping and big data analytics.

Most of the companies use Data Analytics Using Python since it's simple to use language. This field has various chances for the aspiring candidates if they are trying to make their carrier in this field. You just need to think about python. It is a well-known language generally known to increase the productivity level of the developers. Finding out the errors in this language is very simple. In other words, debugging errors in this language is easy as compared to other languages. It also provides a platform to build a different types of games. Several games have been built using this language. Those who have an interest in computers or coding can opt for Data Science Using Python Course in Noida.

Reasons to Learn

Simple Syntax:

The majority of programming languages have simple syntaxes. Programming languages like Java, C++ use syntax in terms of commas, colons, and brackets. The syntax of these languages is used at different places for different-different purposes. It, however, makes it very difficult to carry out a programming code. This is a very simple language as compared to others. No one needed to spend more time in debugging the errors.

Dynamically Typed Language:

While running the code, it comes to know about the type of variables it uses. Hence, it is a dynamically typed language. The type of variable is not clear when you run the code. It stores the variable in its memory and then the variable is known at the run-time.

GUI Based Desktop Application:

This language is used to create a plethora of programs. Since it has discovered, developers have been using it for their benefits. 3ds Max, Paint Shop Pro, etc are created with the help of 2D and 3D imaging software. Abacus is the software that is coded in Python. Many games have been built using this language. It is an important language in the field of data science known for its high speed and productivity.

Job Opportunities after Python Training:

The demand for this language is increasing at a rapid rate in the market. Organizations have been searching for skilled candidates to develop web applications. With Data Science Using Python Training in Delhi NCR, India, a candidate can easily gain some programming skills. The carrier scope in this field is very large. A candidate can be hired as a Python Developer or a Data Analyst or more. Python plays an important role in your resume. Some other job profiles by learning this are Research Analyst, Software Engineer, and Software Developer and so on. Training is a very important part to be a successful developer or researcher. The good part is that Ducat IT Certification are provided on completing the training successfully. It opens a lot of opportunities for aspiring candidates.

Why Ducat?

Ducat has a dedicated team of highly expert trainers to identify, evaluate, implement and providing Best Data Analytics Using Python Training Institute in Noida for our students. Our Trainers leverage a defined methodology that helps identify opportunity, develop the most optimal resolution and maturely execute the solution. We have the best trainers across the world to provide Best Data Analytics Using Python Training in Noida who are highly qualified and are best in their field. The Training & Placement cell is committed to providing all attainable help to the students in their efforts to seek out employment and internships in every field. The placement department works beside alternative departments as a team in molding the scholars to the necessities of varied industries. We got proactive and business clued-in Placement Cells that pride itself on a robust skilled network across numerous sectors. It actively coordinates with every student and ensures that they get placed with purported MNCs among six months of graduating. We are the Best Data Science Using Python Training Institute in Noida.


Python Programming language is a powerful open-source language. It is developed with a data science tool and is used to simplify and easily access the data and store the data easily. By Python Programming language we can easily manipulate the data, also it can help in the analysis of Data, we can create wonderful visualization and helps to access the high-quality content.This Data Science with Python Training provides you to learn data manipulation and cleaning of data using python.

Course Overview

  • Overview of Data science
  • What is Data Science
  • Different Sectors Using Data Science

Data Analytics Overview

  • Exploratory Data Analysis(EDA)
  • EDA-Quantitative Technique
  • EDA - Graphical Technique
  • Data Analytics Conclusion or Predictions
  • Data Types for Plotting
  • Data Types and Plotting

Mathematical Computing with python(NumPy)

  • Introduction to Numpy
  • Activity-Sequence
  • Creating and Printing an ndarray
  • Class and Attributes of ndarray
  • Basic Operations
  • Activity – Slicing
  • Copy and Views
  • Mathematical Functions of Numpy
  • Advance Slicing
  • Transpose and arance
  • Searching

Scientific Computing with Python(SciPy)

  • Introduction of SciPy
  • SciPy Sub Package - Integration and Optimization
  • SciPy sub package
  • Demo - Calculate Eigenvalues and Eigenvector
  • Demo - Calculate Eigenvalues and Eigenvector

Data Manipulation with Pandas

  • Introduction of Pandas
  • Data Types in Pandas
  • Understanding Series
  • Understanding DataFrame
  • View and Select Data Demo
  • Missing Values
  • Data Operations
  • File Read and Write Support
  • Pandas Sql Operation

Python for Data Visualization-Matplotlib

  • Introduction to Matplotlib
  • Matplotlib Part 1 Set up
  • Matplotlib Part 2 Plot
  • Matplotlib Part 3 Next steps
  • Matplotlib Exercises Overview
  • Matplotlib Exercises – Solutions

Python Data Visualization – Seaborn

  • Introduction to Seaborn
  • Distribution Plots
  • Categorical Plots
  • Matrix Plots
  • Regression Plots
  • Grids
  • Style and Color
  • Seaborn Exercise Overview
  • Seaborn Exercise Solutions

Introduction to Machine Learning

  • Link for ISLR
  • Introduction to Machine Learning
  • Machine Learning with Python

Linear Regression

  • Linear Regression Theory
  • Model selection Updates for SciKit Learn
  • Linear Regression with Python – Part 1 Introduction
  • Linear Regression with Python – Part 2 Deep Dive
  • Linear Regression Project Overview and Project Solution

Logistic Regression

  • Logistic Regression Theory – Introduction
  • Logistic Regression with Python – Part 1 – Logistics
  • Logistic Regression with Python – Part 2 – Regression
  • Logistic Regression with Python – Part 3 – Conclusion
  • Logistic Regression Project Overview and Project Solutions

K Nearest Neighbours

  • KNN Theory
  • KNN with Python
  • KNN Project Overview and Project Solutions

Decision Trees and Random Forests

  • Introduction to Tree Methods
  • Decision Trees and Random Forest with Python
  • Decision Trees and Random Forest Project Overview
  • Decision Trees and Random Forest Solutions Part 1
  • Decision Trees and Random Forest Solutions Part 2

Support Vector Machines

  • SVM Theory
  • Support Vector Machines with Python
  • SVM Project Overview
  • SVM Project Solutions

K Means Clustering

  • K Means Algorithm Theory
  • K Means with Python
  • K Means Project Overview
  • K Means Project Solutions

Principal Component Analysis

  • Principal Component Analysis
  • PCA with Python

Recommender Systems

  • Recommender Systems
  • Recommender Systems with Python – Part 1 The Foundation
  • Recommender Systems with Python – Part 2 Deep Dive

Natural Language Processing

  • Natural Language Processing Theory
  • NLP with Python
  • NLP Project Overview
  • NLP Project Solutions

Big Data and Spark with Python

  • Big Data Overview
  • Spark Overview
  • Local Spark Set-Up
  • AWS Account Set-Up
  • Quick Note on AWS Security
  • EC2 Instance Set-Up
  • SSH with Mac or Linux
  • PySpark Setup
  • Lambda Expressions Review
  • Introduction to Spark and Python
  • RDD Transformations and Actions
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