Artificial Intelligence Course by Algoritmolab

Advanced Deep Learning for

Artificial Intelligence

Learn the fundamentals of Mathematics to advanced implementations of Deep Learning in various real-life applications of Artificial Intelligence from experienced industry experts and faculties from top institutions

Live Online Class

Hands-On Lab

Class Recordings

e-Learning Materials

Learn the fundamentals of Mathematics to advanced implementations of Deep Learning in various real-life applications of Artificial Intelligence from experienced industry experts and faculties from top institutions

Live Online Class

Hands-On Lab

Class Recordings

e-Learning Materials

 Course Overview Course Overview

This rigorous 48-hour blended program with online live lectures and hands-on sessions covers the fundamentals of deep learning maths to advanced deep learning for Artificial Intelligence (AI) applications.

Start your learning journey from the basics of mathematical understanding, and neural networks from scratch and gain in-depth knowledge on convolutional neural networks, recurrent neural networks, long short-term memory, autoencoders and generative adversarial networks to use them in computer vision and natural language processing applications.

Prerequisite Prerequisite

Students must have completed 12th grade high school Mathematics

Basic programming skills in at least one programming language, preferably in R or Python

Basic understanding of Data Science and Machine Learning algorithms

Course Content Course Content

Maths for Deep Learning

Introduction to Matrix

Matrix Computation

Vector Algebra

Basics of Calculus

Basics of Probability

Numpy for Deep Learning

Using Numpy for Matrix Computation

Using Numpy for Calculus & Probability

Scalar, Vector, Matrices & Tensors

Functions & Convex Optimization

Neural Network

Introduction to Neural Network

Loss Functions

Building Blocks of Neural Network

Forward and backward propagation


Implementing neural network from scratch

Implementing neural network with Keras

Training your first deep neural network

Convolutional Neural Network

Introduction to Convolutional Neural Network

Working with Images

CNN Building Blocks

CNN Architectures

Understanding Strides and Padding

Understanding Pooling Layers

Semantic Segmentation

Object Detection

Bounding Box

Building a CNN using TensorFlow & Keras

Computer Vision

Intro to OpenCV

Automated Optical Inspection

Object Segmentation & Detection

Object Classification

Object Localization

Face Recognition

Recurrent Neural Network’

Introduction to Recurrent Neural Networks

Comparing RNN with Hidden Markov Model

Understanding how Recurrent Neural Networks work

RNN Architectures

Forward Propagation

Backward Propagation through Time (BPTT)

Checkpoints & Early Stopping

Building a RNN using TensorFlow & Keras

Long Short-Term Memory (LSTM)

Problems in Sequence Predictions

Limitations of Multi-Layer Perceptrons & RNN

The Long Short-Term Memory Network

Backpropagation Training

Backpropagation through Time

Truncated Backpropagation through Time

Developing a LSTM with Keras

Developing a CNN LSTM

Developing Bi-Directional LSTM

Diagonise & Tune LSTM

Natural Language Processing

Intro to Statistical NLP Techniques

Natural Language Understanding

Working with Texts – Tokenization, Stemming, Lemmatization

Word Embeddings – Word2Vec

Word Embeddings – POS Tagging

Word Embeddings – Names Entity Recognition

Word Embeddings – TF-IDF

Natural Language Generation

NLP Applications

Implementing Autoencoders with Keras

Implementing Simple AutoEncoders

Dimensionality Reduction using AutoEncoders

Denoising Autoencoders

Changing Black & White Images into Color Images

Deep Generative Models

Generating Images with GANs

Implementing DCGANs

Implementing Variational Autoencoders

view more...

Faculty Members

Dipayan Sarkar

Senior Data Scientist, Ex-Maersk

Adjunct Faculty, Great Learning, Chennai and BML Munjal University, Gurgaon

With over 20 years of experience, Dipayan has a wealth of knowledge under his belt when it comes to analytics in real-world situations. Prior to being an independent consultant and a mentor in the Data Science, Machine Learning (ML) and AI space with various organizations, universities, and educational institutions, he served in the capacity of a senior data scientist with various Fortune 500 companies. He also holds a Masters in Economics.

Over the last decade, he has focused his analytics expertise in the fields of Data Science, ML and AI as he has found how passion, technology and analytics can be combined to create products that are essential in today’s business environment. Dipayan takes a keen interest in the mathematics behind the ML techniques.

While consulting for corporations on their Data Science and Analytics requirements, he is also a current content developer, mentor and trainer in the Data Science, ML, and AI space with premier institutions such as Great Learning, Amity University, BML Munjal University.

Swarna Gupta holds a B.E. in computer science and has six years of experience in Data Science space. She currently works as a data scientist with Rolls Royce. Her work revolves around leveraging Deep Learning and Machine Learning and AI for various business functions.

She has extensively worked on IoT-based projects in the vehicle telematics and solar manufacturing industries. During her current stint with Rolls Royce, she has implemented various Deep Learning techniques to build advanced analytics capabilities in the aerospace domain.

Rehan Ali Ansari has a Bachelors in Electrical and Electronics Engineering with five years of experience in Data Science. He is currently a Data Scientist at AP Moller Maersk Group, focusing on digital competency.

Rehan has a diverse background of working across multiple domains such as fashion retail, IoT, renewable energy, trade finance and supply chain management. He constantly keeps himself updated with the latest technologies in the field of data science.

Course Fee


(Usual Price ₹51,000 +GST)

Course Certificate Course Certificate

Participants get a course completion certificate upon passing an examination

The examination is conducted by Algoritmo Lab

Rescheduling of examination is allowed

The course fee is inclusive of the examination fee

AI Certificate