Ignite your data-driven journey! Join our immersive course in

Data Science, Machine Learning, and Deep Learning with Python.

From image processing with OpenCV to mastering CNN and YOLO models , we cover it all
Unlock the Power of Data: Data Science, Machine Learning, and Deep Learning with Python

In this comprehensive course, you will delve into the foundations of data science and machine learning, unraveling the mysteries behind algorithms and their applications.

you'll be learning both supervised and unsupervised learning algorithms, from linear regression and decision trees to clustering.

Ever wondered how computers "see" objects? With our course, you'll explore the realm of convolutional neural networks (CNN), the revolutionary technology behind image classification.

But that's not all – Dive into the captivating realm of the YOLO (You Only Look Once) model, a groundbreaking object detection algorithm. Learn how to identify and locate objects in images and videos.
Unleash your creativity and apply Transfer Learning techniques to customize the YOLO model for your specific needs.

Upcoming Batches



Batch Start Date:Mon Apr 15 2024

Batch Time:

1. 7:30 AM to 9:00 AM

2. 6:00 PM to 7:30 PM



Apply Now



Batch Start Date:Thu May 23 2024

Batch Time:

1. 7:30 AM to 9:00 AM

2. 6:00 PM to 7:30 PM



Apply Now

What you'll learn

This curriculum designed by Industry expert for you to become a next industry expert. Here you will not only learn, you will implement your learnings in real time projects.

Basic Python and It's Fundamental Concept
1 Weeks

Discover the magic of Python by effortlessly installing it and setting up your development environment.

After Installing Python we will be mastering the following fundamental Concepts.

Hello! World Program

Data Types




Control Flow


Functions and Modules

Functions and Modules

File handling


For Each topics, we will do hands on practice by solving many programs which will help you to build your logics and Increase your Imagination Power.

Data Science - Working with Data
2 Weeks

Explores data manipulation and analysis using Python. Focuses on NumPy for numerical computing, including creating and manipulating arrays. Introduces Pandas for data manipulation, cleaning, preprocessing, and exploratory data analysis.

Working with Data

Introduction to data manipulation and analysis.

Creating and manipulating arrays - NumPy

Introduction to Pandas for data manipulation

Data structures (Series, DataFrame)

Data cleaning and preprocessing techniques.

Data Visualization - MatplotLib & Plotly

Introduction to data visualization and its importance

Matplotlib for 2D plotting - Line plots, scatter plots, bar plots, histograms and more.

Categorical plots, distribution plots, regression plots with Seaborn.

Plotly for interactive and web-based visualizations.

Creating interactive plots and dashboards

Image Processing with Python & OpenCV
1 Weeks

Introduces image processing and computer vision concepts. Students learn to work with the OpenCV library in Python, including image reading, writing, manipulation, and filtering.

Introduction to image processing and computer vision.

Installing and using the OpenCV library in Python

Introduction to Pandas for data manipulation

Image reading, writing, and manipulation

Image filtering techniques (blurring, sharpening, thresholding)

Feature extraction techniques (edge detection, corner detection)

Object detection using Haar cascades

After this section we will create face detection project, where we will trainig our machine with multiple faced, and detect the correct face.

Play with Machine Learning
2 Weeks

Provides an introduction to machine learning and focuses on supervised learning algorithms. Students learn to build and evaluate models for regression and classification tasks.

Lern different algorithms of supervised learning.

Introduction to machine learning and supervised learning.

Simple linear regression, multiple linear regression

Model evaluation metrics (mean squared error, R-squared)

Logistic regression for binary classification.

Gradient descent optimization algorithm

Naive Bayes for probabilistic classification

Linear SVM, kernel trick, nonlinear classification.

K-Nearest Neighbors (KNN) algorithm.

Decision Trees for classification and regression

Explores unsupervised learning algorithms, specifically clustering. Covers K-means Clustering and Hierarchical Clustering. Students learn to group data based on similarities and evaluate clustering performance.

Fun with un-supervised learning.

Clustering algorithms overview

K-means Clustering for grouping data

Elbow method for cluster evaluation.

Hierarchical Clustering for creating tree-like clusters.

Deep Learning - TensorFlow and Keras
2 Weeks

Introduces the fundamentals of deep learning. Covers artificial neural networks, backpropagation algorithm, and building multi-layer networks with Keras. Includes topics like activation functions, weight initialization, and model saving/restoring.

Deep Learning Fundamentals

Introduction to artificial neural networks (ANN)

Perceptron and activation functions

Feedforward neural networks and forward propagation

Multi-layer networks with Keras

Activation functions, weight initialization, regularization

Saving and restoring a trained model for future use

Advanced Deep Learning

Introduction to Convolutional Neural Networks (CNN)

CNN architectures: AlexNet, VGGNet, InceptionNet, ResNet

Convolutional layers, pooling layers, fully connected layers.

Introduction to Generative Adversarial Networks (GAN)

Training GANs for image generation and manipulation

Transfer Learning and Image Classification

Introduction to transfer learning

Using pre-trained models and transfer learning with Keras

Working with the ImageNet dataset

Building image classification projects using transfer learning

Fine-tuning pre-trained models

Machine Learning is Exciting: Inspiring Projects
1 Weeks

Get ready to supercharge your AI - ML journey with a collection of exciting and practical project ideas.

During the learning, we will develop some mini projects like,

1. Movie Recommendation

2. Stock Price Prediction

3. Iris Flower Classification

4. Digit Recognition

5. Handwritten Digit Generation

Apart from these basic app, we will create 3 advanced projecs.,

Fruit Image Classifier.

Mask Detection of Face

Gender Recognition

Image Style Transfer : Color the image

"Your ideas matter to us! We welcome captivating project suggestions to enhance our training.

Let's collaborate on creating an engaging and impactful learning experience that brings your ideas to life and develops valuable skills.

Technologies You Will Master Hands-On

During this program you will learn some most demanding technologies. We will develop some real time projects with the help of these technologies.








Scikit Learn













Program Fees


(incl. taxes)

If you will join in a group, complete group will get discount.

You can pay your fee in easy installment's. For more details you can connect with our team.

Meet Your Instructors

You will learn with industry expertes.

Prateek Mishra

Prateek Mishra

CTO & Sr. Trainer

Ex -

Prateek Mishra
Nikita Choudhary

Nikita Choudhary

Director - Training

Ex -

Nikita Choudhary
Atul Malhotra

Atul Malhotra

Sr. Training Manager
Atul Malhotra

What You Could Become

Transform Into a Full Stack Data Scientist - Your Path to Limitless Possibilities!

Data Scientist

Data Analyst

Data Engineer

Data Architect

Statistical Analyst

Machine Learning Engineer

Deep Learning Engineer

And many more...

Frequently Asked Questions

What software and tools will I need for the course?

You will need a computer with an internet connection and a code editor. We will guide you on how to set up the necessary software and tools during the course.

How long is the course, and what is the learning format?

The course duration can vary depending on the format chosen, such as full-time, part-time, or online. Typically, the course is conducted over a period of weeks or months with a specified number of hours per week.

Will I receive a certificate upon completing the course?

Yes, upon successful completion of the course, you will receive a certificate that demonstrates your proficiency in this course

Is the course self-paced or instructor-led?

The course is typically instructor-led, with structured lessons and hands-on exercises. However, the specific format may vary depending on the learning platform or institution offering the course.

Can I ask questions and seek help during the course?

Absolutely! The course usually includes opportunities to interact with instructors and fellow learners through discussion forums, chat platforms, or live sessions. You can ask questions, seek clarification, and receive guidance throughout your learning journey.

Can I take this course if I am a beginner in this field?

Absolutely! This course is designed to cater to both beginners and experienced developers. We start with the fundamentals and gradually progress to more advanced topics.