Master Deep Learning With Industry Experts
Industry-focused AI & Deep Learning program covering Neural Networks with TensorFlow, TensorBoard, and advanced Deep Learning concepts with intensive 4-day classroom/LVC training + 3 months of LIVE project mentoring and unlimited access to Data Science Cloud Lab for hands-on practice.
Choose Your Learning Path
Flexible Plans Designed to Fit Your Schedule & Learning Style
Select the learning mode that works best for you — self-paced, live online, or in-person classroom training
Blended Learning
Self Learning + Live Mentoring
- Self Learning + Live Mentoring
- NASSCOM & IBM & AAAI Certification
- 1 Year Access to E-learning
- 25 Capstone & 1 Client Project
- Job Assistance
- 24x7 Learner Assistance
Live Virtual
Instructor Led Live Online
- NASSCOM & IBM & AAAI Certification
- 7-Month | 700 Learning Hours
- 120-Hour Live Online Training
- 25 Capstone & 1 Client Project
- 365 Days Flexi Pass + Cloud Lab
- Placement Assurance
Classroom
In-Person Classroom Training
- NASSCOM & IBM & AAAI Certification
- 7-Month | 700 Learning Hours
- 120-Hour Live Online Training
- 25 Capstone & 1 Client Project
- Cloud Lab Access
- Placement Assurance
Tools & Technologies
Master Industry Tools
Hands-on training on the tools and technologies used by top data teams
worldwide.
Certification
NASSCOM & IBM & AAAI Certification
Flexible Financing Options
Pay in Easy Installments at 0% Interest
We’re dedicated to making our programs accessible. No hidden costs, transparent pricing
EMI Available
ShopSe
No Cost EMI & Scholarships Available
Our Partners
Companies That Hire Our Graduates
200+ leading companies trust Data Sprint graduates to drive their data
initiatives.
Why Data Sprint
Why Thousands Choose Data Sprint
We’re committed to transforming careers with quality education and real-
world experience.
Course Syllabus
Comprehensive Data Science Curriculum
A structured learning path covering foundations to advanced topics across data science, machine learning, and AI.
Tensorflow Essentials
• Introduction to TensorFlow
• Computational Graph
• Stochastic Gradient Descent
• Visual TensorBoard
• Keras with TensorFlow
Python Foundation – 4 Modules
• Role of Activation functions in ANN network
• Activation Functions:
• Sigmoid (Binary)
• Softmax (Multiclass)
• ReLU (Linear)
Artificial Neural Networks
• Introduction to ANN
• Concept of Perceptron
• Perceptron Training Rule
• Gradient Descent Rule
Gradient Descent And Backpropagation
• Gradient Descent
• Stochastic Gradient Descent
• Backpropagation
• Some problems in ANN
Optimization And Regularization
• Overfitting and Capacity
• Cross Validation
• Feature Selection
• Regularization
• Hyperparameters
Introduction to Convolutional Neural Networks (CNN)
• Introduction to CNNs
• Principles behind CNNs
• Kernel and Multiple Filters
• CNN Image Classification demo
Introduction to Recurrent Neural Networks (RNN)
• Introduction to RNNs
• Unfolded RNNs
• Seq2Seq RNNs
• LSTM
• RNN applications
Deep Learning Applications
• Image Processing
• Natural Language Processing
• Speech Recognition
• Video Analytics
Deep Learning Projects (Hands On)
• Image Classification with CNN – Keras
• Natural Language Processing with NKTL live project
Not Sure Which Course Is Right For You?
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