Overview
We have designed a Flexible program for you
Missed a class?
Watch the recording later with teaching assistants available to
solve your doubts
Feeling left behind?
We have created a collaborative learning environment with peer
learning and group projects
Job & class timings clash?
Flexible class timings to choose from based on your availability
Want to practice?
Study materials, quizzes, projects and mock interviews are
provided to ease the process
Have doubts?
Reach out anytime - ours Mentors and teaching assistance will
always be ready to help
Who is this course for?
Applicable to anyone who is interested to learn ML and AI, even to
people with minimal or no coding background.
UG/PG students trying to land a job.
Professionals trying to switch career.
Professors trying to skill up to teach and learn for their
research purposes.
People on a career break, to get acquainted with the latest
technology.
Why yet another AI course?
All the resources required to become a Data scientist are
available online for free. But when students come across a complex
Math Equation or Algorithm, they tend to lose confidence and drop
out.
On the other hand there are very expensive courses (2L to 3L), which are way out of reach to the common people. Those programmes are also based on recorded videos with once a week live Mentoring session.
AIFab50 offers you live classroom-like training with 1 to 1 mentorship to follow up daily, at a very nominal cost.
On the other hand there are very expensive courses (2L to 3L), which are way out of reach to the common people. Those programmes are also based on recorded videos with once a week live Mentoring session.
AIFab50 offers you live classroom-like training with 1 to 1 mentorship to follow up daily, at a very nominal cost.
Course Duration?
It has been planned in such a way that you get time to learn and
solidify your learning through implementation.
4 months
(16 weeks live classroom training)
+2 months
(Project Mentorship/Internship)
We don't leave you
(Career Guidlance)
We will create a scenario
(Job Assistance)
Who Created this course?
Navaneeth Malingan and Team
Navaneeth is the Founder & Director of Nunnari labs. He leads the
AI Innovation at Nunnari Labs and empowers people through
education via Nunnari Academy. He has impacted over 10,000+
students through different channels and communities. He has
extensive experience in Software Engineering, Data Analysis,
Machine Learning, Deep Learning, Computer Vision, NLP and MLOps.
He is involved in building real world AI Solutions and also does
Corporate Training, Workshops and Faculty Development Programs.
Navaneeth is a Tech Evangelist and Thought Leader, putting to action his plans and vision through Nunnari labs, an emerging startup with aspiring goals to provide Industry 4.0 solutions.
Navaneeth is a Tech Evangelist and Thought Leader, putting to action his plans and vision through Nunnari labs, an emerging startup with aspiring goals to provide Industry 4.0 solutions.
Meet Your Instructors
Cathrine Jeeva
Instructor/Mentor
Machine Learning Engineer @ Nunnari Labs
Key Features
How the course benefits the students and why they should opt in
Online
100% Live Classroom session
1 to 1
Expert Mentoring in English and தமிழ்
Help
Our expert team will always be available to help you
Hiring
Top performers will be hired under the R&D sector
Tailor Made
For different groups like Students, Academicians and Software
Engineers
Community learning
You will be a part of the learning community, even after
course completion
What will you be Learning?
AIFab50 covers
Artificial Intelligence Technologies
Machine Learning
Mathematics for Machine Learning
Deep Learning
Computer Vision
Natural Language Processing
Tools Covered?
You will use the latest Tools and Frameworks which are used in the
Industry.
Python Libraries
Visualisation Libraries
Deep Learning
Natural Language Processing
Demo Videos?
Checkout our previous classes
Training Curriculum?
Checkout the full syllabus here
Python for Data Science
- Python Basics
- Numpy
- Pandas
- SciKit Learn
- Matplotlib, Seaborn, Plotly
Mathematics for Machine Learning
- Linear Algebra
- Multivariate Calculus
- Descriptive Statistics
- Probability & Distributions
Machine Learning
- Supervised Learning
- Unsupervised Learning
- Ensemble Techniques
Deep Learning
- Multi Layer Perceptrons
- Convolutional Neural Networks
- Recurrent Neural Networks
- Transformers
- Tensorflow and Keras
Computer Vision
- Convolutional Neural Networks
- Convolution, Pooling, Padding & its mechanisms
- CNN architectures like LeNet, AlexNet, VGGNet, InceptionNet & ResNet
- Transfer Learning
- Data Augmentation
Advance Computer Vision
- TensorFlow Functional API
- Object Detection
- YOLO, R-CNN, SSD
- Semantic Segmentation
- U-Net
- Face Recognition using Siamese Networks
- Instance Segmentation
NLP Basics
- Introduction to NLP
- Stop Words
- Tokenization
- Stemming and lemmatization
- Bag of Words Model
- Word Vectorizer
- TF-IDF
- POS Tagging
- Named Entity Recognition
Sequence Models and NLP
- Introduction to Sequential data
- RNNs and its mechanisms
- Vanishing & Exploding gradients in RNNs
- LSTMs - Long short-term memory
- GRUs - Gated recurrent unit
- Sequence to Sequence Models
- Attention mechanism
- Neural Machine Translation
- Transformers and Self-Attention
- Transformers, BERT, GPT-2
Earn a verified Certificate of Accomplishment
On course completion you will be issued with a certificate that
you can showcase on your Résumé and LinkedIn profile.
Our Alumni Work At
Our students have excelled and are now employed in top MNCs.
Testimonials from our Learners
Hear from our previous batch students
Swathi Durai
Student
Coimbatore Institute of Technology
Rajasimman
Professional | Android Developer
TVS
N.Nithya
Associate Professor
Sona School of Management
Deepika Gurung
Student
Sona college of technology
Cathrine Jeeva
Sri Krishna College of Arts and Science
TCS
Harini Sivakumar
Student
SNS college of technology
Prabhhav Sharma
Fresher
Karunya University
Apply Now!
We succeed only when you do. We will support your job search in
several ways, starting from Day 1 of the program.
