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Deep Learning with Python

Live Online (VILT) & Classroom Corporate Training Course

Deep learning is a machine learning technique that clarifies computers to do what comes naturally to humans. In deep learning, a computer model studies how to perform classification jobs directly from images, text, or sound.

Expert-Led VILT & Classroom Hands-On CloudLabs Certification Voucher Available
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Overview

Deep learning is the most powerful Machine learning method in various areas such as Robotics, Natural Language Processing, Image Recognition and Artificial Intelligence. The Deep Learning using Python course is designed for anyone with at least a year of coding experience and knowledge in mathematics.

Objectives

At the end of Deep Learning with Python training course, participants will learn

  • Fundamentals of Deep Learning techniques
  • Artificial Neural networks and their architecture
  • Building and training the deep neural networks from scratch.
  • Convolutional Neural Networks (CNN)
  • Different optimization techniques to tune the learning of any neural network
  • Pointers to next frontiers in CNN and Deep Learning

Prerequisites

Basic python programming skills. Basic mathematics skills. Basic knowledge of Machine learning fundamentals

Course Outline

  • Introduction to DL problems
  • DL terminologies
  • DL project workflow
  • DL real life examples

  • Working with Jupyter notebooks
  • Markdown and Code blocks
  • Keyboard shortcuts

  • Python syntax
  • Basic data types
  • Basic data structures

  • Numpy Arrays
  • Plotting using Matplotlib
  • Pandas Dataframes
  • Introduction to Keras

  • What is a Neuron
  • What are Activation Functions
  • How does a neural network learn?
  • Gradient Descent
  • Stochastic Gradient Descent
  • Back Propagation
  • Artificial Neural Networks in Keras
  • Linear model (No Hidden Layers)
  • Neural network with a single hidden layer

  • Image representation
  • ConvNets or CNN
  • Convolution Layer
  • Padding
  • How do we learn these kernels?
  • Can we force a particular kernel to learn to recognize a specific feature?
  • Non-Linear Activations
  • Downsampling or Pooling
  • Full Connection
  • Loading MNIST data
  • Implementation of CNN in Keras

  • Introduction to Auto Encoders
  • Why learn identity function?
  • Properties of learned function
  • Real world applications of Autoencoders
  • MNIST Dimensionality Reduction
  • A Simple Autoencoder
  • Functional API
  • Deep Autoencoder
  • Convolutional Autoencoder
  • Image Denoising
  • Data Specific Encoding and Decoding

  • Introduction to Recurrent Neural Networks
  • Sequence Learning
  • Regular Neural Network
  • Simple RNN
  • Problems with RNN
  • Long Short Term Memory (LSTM)
  • Stacked (Deep) LSTM Model
  • Deep Stacked LSTM with Stateful Cells
  • Gated Recurrent Unit

Available Training Modes

Pick the format that fits your team.

Same authorised curriculum, same trainers, same hands-on cloud labs — delivered the way that works for you.

Live Online (VILT)

Real-time instructor-led sessions over Zoom or Teams. Same classroom, different time zones.

Most popular

Classroom

Face-to-face training delivered at your office, our Bengaluru centre, or any partner venue worldwide.

Onsite

Self-Paced

Recorded sessions plus 24/7 access to cloud labs and assessments. Learn at the pace that works for each engineer.

On-demand

Blended

Live workshops with self-paced reinforcement and project-based labs. Best for hybrid teams across regions.

Hybrid teams
All modes include: hands-on cloud labs, recordings, assessments, certificate of completion. Talk to a solutions advisor →

Our Training Process

How a course becomes measurable skill.

One contract, five steps, zero handoffs. From discovery to deployment, the same Synergific team owns the outcome — not a chain of vendors.

5 Steps from your scoping call to certified, productive engineers.
01

Discover & set goals

We start with a scoping call to understand your team's current skill level, target outcomes, deadlines, and certification needs — then translate that into a measurable success plan with named owners on both sides.

02

Curate the right path

We map the optimal learning path — instructor-led, self-paced, or blended — with hands-on cloud labs, prerequisite refreshers, and certification vouchers built in. No filler modules, no padded curriculum.

03

Deliver hands-on training

Authorised trainers run live sessions backed by 24/7 cloud labs and real-world projects. Theory and practice on the same day — learners stop forgetting concepts before they get to apply them.

04

Assess & mentor

Continuous skill checks, mock exams, and 1:1 mentoring keep the program honest. If anyone falls behind, we course-correct in-flight — you'll never find out at the end that two engineers couldn't keep up.

05

Certify & apply on the job

Voucher-backed certification, post-training office hours, and 30-day reinforcement so skills land on real work — not just on the exam scorecard. Success measured after the course ends, not before.

Client Stories

What our clients say

Voices from L&D leaders, architects, and program managers who’ve trusted us with their upskilling.