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Why You Should Learn Data Science?

Highest Salaries

Increasing Demand

Fastest Growing

Suitable even for Non-Tech People

10+ Industry Needed Topics Covered in this Courses

Chatbot
(Using Google Dialogflow)

Excel

PowerBI

Tableau

Python

Machine Learning

Deep Learning

Ideas on A.I Cloud

MySQL

MongoDB

Ideas on A.I Hardware

NLP

Bonuses You Can Get If You Enroll Before Offer Ends

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NEW

Complete Course Fee

5999 ₹ 999
  • 4 Courses - Topic-Wise Video Lectures (Artificial Intelligence + Data Analytics + Machine Learning)
  • 45+ Capstone Projects Hands-on
  • Saturday Zoom Live Q&A Session + New Lectures on the current trend
  • 45+ Source Code Download
  • Lectures on 10+ Industry needed Topics
  • 4 Internship certificate

  • (If You Registered before Offer Ends)
  • Interview Q&A PDF Collections
  • Softskill Coaching (Interview skills, Communication skills, Mindset)
  • Lifetime Private Community
  • Sample Resumes
  • Entrepreneurship Program
Register here to enroll all the features

Real comments from real peoples

Enroll Now 4 Internship @999/- ONLY
(Offer Ends Today)

For Whom this course is ?

  • College students from any department
  • Professors who need to enrich their knowledge to the Industry level & Who wanted to change their career
  • People already working in the Data, who need to get hike by upgrading their knowledge to become Data Analyst / Data scientist
  • People who completed college and looking for High paid & Most Demand Jobs

No Prior Coding Experience Required.

Let's Talk About Numbers

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Products (College & Industry Kits)
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Years Experience
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Google reviews

Meet the Course Designer

A P Sanjay Kumar

Expertise

Programming: Python, C, C++, R, Matlab, Basic Embedded C
Technology: Data Science (Core), Brain-Computer Interface, Blockchain, Robotics, ROS, IOT, Embedded System
Hardware: Nvidia AI Dev Boards, Raspberry Pi, PYNQ FPGA, Intel NCS, Autonomous Robot with LIDAR, ROS on Matlab & Raspberry Pi, Arduino & Other ESP Boards.

Complete Course Curriculum

( Everything Covered From Basics )

Python Bootcamp

In this Session we will be Introducing to Python ,Installing & Working with Python IDLE ,Configuring Environment Variables – Command Window ,Installing Anaconda Navigator (Jupyter Notebook) ,Working with Anaconda Navigator (Spyder Notebook), Working with Google Colab, Working with Pycharm , Working with Libraries

Simple Arithmetic ,  Introduction to Strings , Indexing and Slicing with Strings , String Properties and Methods, Print Formatting with Strings

In this section we will be practising Lists , Dictionaries, Tuples , Sets , Booleans, I/O with Basic Files in Python , Python Objects and Data Structures ,Comparison Operators , Chaining Comparison Operators in Python with Logical Operators , If Elif and Else Statements , For Loops , While Loops , Useful Operators, List Comprehensions , Methods and the Python Documentation.

Introduction to Functions, Basics of Python Functions , Logic with Python Functions , Tuple Unpacking with Python Functions , *args and **kwargs in Python, Lambda Expressions, Map, and Filter Functions , Attributes & Class Keywords.

In this section you will see Class Object Attributes and Methods , Inheritance and Polymorphism , Special(Magic/Dunder) Methods , Modules and Packages , name and “main”

In this section you will see Errors and Exceptions Handling , Pylint Overview , Decorators with Python Overview , Generators with Python, Python Collections Module , Opening and Reading Files and Folders

In this section you will see Python Math and Random Modules , Python Debugger , Python Regular Expressions , Timing Your Python Code

In this section you will learn Zipping and Unzipping files with Python ,Setting Up Web Scraping Libraries, Grabbing a Title, Grabbing an Image, Book Examples

In this section you will see Introduction to Images with Python,  Working with CSV Files in Python, Working with PDF Files in Python , Python Datetime Module , Sending Emails with Python

In this section we will be creating a GUI for an application and Bonus codes will be discussed. 

Artificial Intelligence Master Class

In this section you will see the overview of this course | Introduction to AI | How to create basic AI applications (Chatbot using DialogFlow).

In this section, You will learn the various components in capture cis and how design schematics.
How to create project. How to link library and finally how to draw Schematics.

In this section you will see Introduction to Computer Vision and How to install computer vision libraries.

Here you will have a practical section on how to detect moving object with the help of its color based on OpenCV techniques.

In this section you will see how to detect and track a face in real time using Haar Cascade Algorithm.

In this section you will see how to track an object using color with opencv techniques.

In this section you will see how to Recognize different Faces in real-time.

In this section you will be able to recognize different face emotions using OpenCV techniques.

In this section you will see the introduction about deep learning and how to install different libraries required for deep learning.

In this section you will be able to design your own neural network based on the requirements.

In this section, you will be able to recognize different objects with the help of pre-trained models.

Here you will be using convolutional neural network to classify different image labels

In this section you will be able to recognize different hand gestures using deep learning.

Here you will be able to perform leaf disease detection using Convolutional neural network

In this section you will be able to recognize different characters using CNN

Here you will able to read different characters using optical character recognition

In this section you will be practicing smart attendance marking system using Deep learning Techniques in real time

Here you will be able to detect different vehicles using deep learning techniques.

Here you will be Deploying an ALPR Application using Open ALPR.

In this section you will be detecting drowsiness using 68-Landmark Predictor

Here you will be practicing Road Sign Recognition using Deep Learning technique

In this section you learn about Machine learning| How to install required Machine Learning libraries

Here you will be evaluating different machine learning models by training and deploying it for a particular application.

Here you will be using Machine learning techniques to detect fake news

In this section you will be using Reinforcement technique to design an AI based Snake game.

In this section you will have an Introduction to NLP & it’s Terminology and How to install NLP Libraries NLTK

Here you will be generating titles from paragraph using NLP Technique

In this section you will be able to analyze the Speech and also detect the emotion using NLP Techniques

Here you will learn Cloud-based AI, Object recognition using Amazon Web Service (AWS) & Imagga

In this section you will Deploy AI application in Raspberry Pi with Neural Compute stick & Nvidia Jetson Nano

Data Analytics Master Class

In this section  you will have an overview of artificial intelligence , Data Analytics & Road Map to become a Data Scientist

In this section you will see how to create Power Query and Tables

In this section you will see how to use different Formula & Pivot Table

In this section you will create Different Chart and dashboard for sales data visualization

Here in this section you will see how to Do automation in excel using VBA MAcros and Power Query

Here in this section you will see some examples related to Descriptive statistics – Mean, Mode, Median, Quartile, Range, InterQuartile Range, Standard Deviation

In this section you will see some examples related to Permutations, Combinations

In this section you will see some examples related to Population and Sampling

In this section you will see some examples related to Probability Distributions – Normal, Binomial and Poisson Distributions

Here you will see some examples related to Hypothesis Testing & ANOVA – One Sample and Two Samples – z Test, t-Test, F Test and Chi-Square Test

Here you will practice examples like how to Connect Tableau to a Variety of Datasets

In this section you will see some examples to Analyze, Blend, Join, and Calculate Data

In this section you will Visualize Data in the Form of Various Charts, Plots, and Maps

Here in this section you will connect tableau to a variety of datasets

Here in this section you will visualize data in the Form of various charts, plots, and maps and calculate data

In this section you will having an Introduction to Python, Installing Python and its Libraries

Here you will be practicing basic python programming required for data analytics.

In this section you will practice some python examples based on numpy

In this section you will practice some python examples based on Pandas

Here you will practice some python examples based on matplotlib for data Visualization 

In this section you will practice some python examples based on Seaborn for data Visualization

Here you will be exploring Kaggle – Dataset, Notebooks and how to participate in Kaggle events

Here you will learn Installing MySQL

In this section you will  learn SQL basics for Data Analytics

In this section you will learn, Installing MongoDB and MongoDB basics

In this section you will have an Overview about Machine Learning and its libraries

In this section You will learn how to evaluate ML algorithm  for classification of State of Electric power system

In this section, Here you will have an Overview about Deep Learning and its libraries

In this section, Here you will learn to design Neural network from scratch for Covid-19 detection

In this section, Here you will get to know about Natural Language toolkit with project Tag Identification

Machine Learning Master Class

In this section you will learn an overview of A.I and Machine Learning

In this section, You will learn How to write code in Google Colab, Jupyter Notebook, Pycharm & IDLE

In this section, You will do project using an algorithm LOGISTIC REGRESSION

In this section, You will do project using an algorithm K-NEAREST NEIGHBOR

In this section, You will do project using an algorithm SUPPORT VECTOR MACHINE

In This section, You will do project using an algorithm NAIVE BAYES

In This section, You will do project using an algorithm DECISION TREE

In This section , You will do project using an algorithm RANDOM FOREST

In This section , You will be  Evaluating Classification model Performance using CONFUSION MATRIX, CAP CURVE ANALYSIS & ACCURACY PARADOX

In This section , You will do project using all ML algorithm to choose best model to classify breast cancer

In This section ,You will do project using an algorithm LINEAR REGRESSION

In This section ,You will do project using an algorithm LINEAR REGRESSION

In this section, You will do project using  POLYNOMIAL REGRESSION algorithm

In this section, You will do project using an algorithm SUPPORT VECTOR REGRESSION

In this section,You will do project using an algorithm DECISION TREE REGRESSION

In this section, You will do project using an algorithm  RANDOM FOREST

In this section, You will be Evaluating Regression model performance using R-SQUARED

INTUITION & ADJUSTED R-SQUARED INTUITION

In this section we will be evaluating various regression model for engine energy prediction

In this section, You will do project using an algorithm K-MEANS CLUSTERING

In this section, You will do project using an algorithm HIERARCHICAL CLUSTERING

In this section, You will do project using an algorithm PRINCIPLE COMPONENT ANALYSIS

In this section, You will do project using an algorithm SINGULAR VALUE DECOMPOSITION

In this section, You will do project using an algorithm APIRIORI

In this section, You will do project using an algorithm  ECLAT

In this section, You will do project using an algorithm UPPER BOUND CONFIDENCE

In this section, You will do project Sentimental Analysis using NLTK

In this section, You will do project using an algorithm XGBOOST

In this section, You will learn to design ANN architecture

In this section, You will learn to design CNN architecture

In this section, You will do project using REINFORCEMENT LEARNING

What are you waiting for ?

Start Your Data Science Journey Now

Enroll Now 4 Internship @999/- ONLY
NOTE: Enroll before Offer Ends and get this Discount Course Offer with all the Bonus Features.

Course Completion Certificate

Frequently Asked Questions

  • People are facing problem in the field of learning. A problem such as Not application basis, not interactive, not result-oriented, not hands-on, not precise, etc. these problems were solved in our new methodology of learning “Application-based Learning”
  • You will be part of a Technical private community that delivers Technical skills, soft skills, Mindset, to the Membership
  • You will get the latest interview Q&A mail and also information about jobs and we will keep you motivated!

We are providing Job announcements and guidance to get Job including technical skills and soft skills

This course has been designed to keep beginners in mind. You will be able to learn as we start from the basics. We have many learners doing this course who had no prior coding experience.

Course validity is 1 Year, the reason for not giving the course for a lifetime is We no need number of course registration, we need course completion. As per the human mindset, whenever we have a deadline, we are used to completing the task faster than without a deadline. This is a proper mindset.

But You gonna get Lifetime Validity for the Private Community

Save Your Lakhs of Rupees

Become Data Scientist @ just 3996/- 999

Enroll Now 4 Internship @999/- ONLY
NOTE: Enroll before Offer Ends and get this Discount Course Offer with all the Bonus Features.
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