Transform Your Career with AI Mastery
Empower Your Future with AI Skills
Corporate Training
Academic Training
Consultancy
AI & Data Science Mastery:
from Python basics to Gen AI
This course gives you hands-on experience with cutting-edge tools in Data Science, Machine Learning, Deep Learning, Computer Vision (CV), Natural Language Processing (NLP), and Generative AI (Gen AI). You'll learn exactly how AI works and, more importantly, how to use it to solve real-world problems and advance your career.
What to expect from this course
Gain a Strong Foundation in AI
- Learn the Basics: Start with core concepts in AI, Data Science, Machine Learning, and Deep Learning, giving you a solid grounding in how AI works.
- Explore Advanced AI Techniques: Dive deeper into specialized areas like Computer Vision, Natural Language Processing (NLP), and Generative AI (Gen AI) to solve complex problems.
- Real-World AI Applications: See how AI is transforming industries like healthcare, finance, and technology through practical examples
Hands-On Experience with Leading AI Tools
- Work on Real Projects: Get hands-on experience by working on real-world projects using popular AI tools like Python, TensorFlow, and PyTorch.
- Master Data Analysis and Model Building: Learn how to handle, analyze, and visualize data, build machine learning models, and evaluate their performance.
- Deploy AI Solutions: Understand the process of deploying AI models into real-world environments, making them usable for businesses.
Acquire Job-Ready AI Skills
- Solve Industry-Relevant Problems: Apply your AI knowledge to real-world challenges, enhancing your problem-solving skills.
- Connect with Industry Experts: Benefit from insights and guidance from AI professionals, learning tools and techniques used by top companies.
- Earn a Recognized Certification: Complete the course and receive a certification that validates your AI expertise and boosts your career prospects.
What you’ll learn on this course
Duration
180 hrs
Capstone Projects
05
Case Studies
11
Tools Covered
23
Course Format
Instructor Led
Study Method
Online | Classroom | Bootcamps
01
Python Fundamentals
16 hrs - Session and 1 Assignment
Python
Anaconda
Jupyter notebook
- Installing Python and Anaconda environment
- Variables, Input Functions, Operators, Control Flow, String Handling
- Data Structures-Lists, Tuples, Sets, Dictionary
- Functions, Modules, Packages, File Handling, Exception Handling
- Object Oriented Paradigms
02
Python Libraries
8 hrs - Session and 1 Assignment
NumPy
Pandas
SciPy
- Numerical Operations – NumPy
- Pandas: Data Frame Basics, Key Operations on Data Frames
- Matrix Operations and Linear Algebra
- Working with SciPy
03
Data Visualization
6 hrs - Session and 1 Assignment
Matplotlib
Seaborn
- Scatter Plot, Line Chart, Histogram, Bar Chart, Box plot, Heat Map, Pair plot
- Scatter Matrix using Matplotlib
- Pandas Visualization
- Seaborn Visualization
04
Statistics and Probability
6 hrs - Session and 1 Assignment
Statsmodels
Statistics - Measuring central tendency, Variance
Probability Distributions - Gaussian, Poisson, Bernoulli, Binomial, Uniform, Exponential
Hypothesis Test, P-Test, t -test, z-Score, Chi-Square Test, ANOVA
05
Time Series Data analysis
6 hrs - Session and 1 Case Study
AutoTs
Darts
- Time Series Data, Seasonal Decompose – Tread, Seasonality
- Down Sampling, Resampling, Up sampling, Time deltas
- Time series forecasting with ARIMA,
- Multivariate Time Series
06
Handling different file formats, Databases
8 hrs - Session and 1 quiz
mySQL
MongoDB
- Working with Different File formats – CSV, JSON, PDF, binary, HDF5
- Interacting with data in SQL-Py SQL with MySQL DB
- Interacting with data in NoSQL -PyMongo with MongoDB
07
Data Cleaning and Data Mining
10 hrs - Session and 1 Case Study
Missingno
Data cleaner
- Data Cleaning -Find and replace missing values & Encoding Categorical Features
- Getting Started with Data Mining
- Affinity analysis
- Recommender Systems
- Market Basket Analysis
08
Machine Learning
26 hrs - Session, 3 Case Studies and 1 Capstone Project
Scikit Learn
OpenAI Gym
- Fundamentals of Machine learning
- Supervised Learning algorithms, Unsupervised Learning algorithms
- Dimensionality reduction, Cross Validation
- Reinforced Learning algorithms
- Working with Scikit-Learn, Train Test, Validation, hyperparameter tuning
- Performance metrics, Save and load the model
09
Getting started with TensorFlow and Neural Networks
6 hrs - Session and 1 Quiz
TensorFlow
- TensorFlow – Loading and exploring the data, Data transformation & Data segmentation, Tensor and Matrix operations
- Neural Networks Foundation, Activation functions, Hidden layers, Illustrate & Training a Perceptron, Important Parameters of Perceptron
10
Deep Learning
24 Lectures, 2 Case Studies and 1 Capstone Project
Keras
- Multi-Layer Perceptron (MLP) Convolutional Neural Network (CNN)
- Recurrent Neural Network (RNN), Long Short -Term Memory (LSTM)
- Regression Networks, Auto Encoders, Generative Adversarial Networks (GAN)
- Deep reinforcement learning, Q learning
- Compile, Optimize, Execution using Tensor Flow & Keras,
- Parameters vs Hyper parameter, Hyper parameters Tuning
- Regularization, Optimization, Policy Gradient Methods
11
Computer Vision (CV)
22 hrs - Session, 1 Case Study and 1 Capstone Project
OpenCV
Scikit-Image
Core Image Operations – Acquisition, Enhancement, Restoration
Exposure & Color, Edges & Gradients (Canny). Pyramids & Contours
Histograms
Geometrical Transformations – Morphology & Transforms, Hough Transform, Filtering & Smoothing
Foreground Extraction (Grabcut)
Feature-Based Detection – Keypoints (Harris Corner, SIFT, SURF, ORB), Object Detection & Recognition
Deep Learning in CV-CNN, VGG, Inception, ResNET
12
Natural Language Processing (NLP)
20 hrs - Session, 1 Case Study and 1 Capstone Project
NLTK
Spacy
Text Pre-Processing – N-Grams, TF-IDF, word2vec, Smoothing, Clustering, LSA, Corpus, WordNet, Web Scraping, Regex, Normalization, Tokenization, Stemming/Lemmatization, Stop words, String Distance, NLTK, Spacy
POS Tagging & CFG – POS Tagging, CFG (Context-Free & Probabilistic), Chunking, Sentence Parsing, Dependency Grammar
Information Extraction-Text Classification, Named Entity Recognition (NER), Dictionaries, Sentence Segmentation
13
Generative AI (Gen AI)
22 hrs - Session, 2 Case Studies and 1 Capstone Project
GPT
DALL E
Advanced NLP – NLP Pipeline, Text Similarity, Anaphora Resolution, Word Sense Disambiguation, Sentiment Analysis, Chatbots- Large Language Models, Text Generation, Image Generation
- Prompt engineering, RAG
This course is for you
Newcomers
No prior AI or technical knowledge is required. This course is ideal for anyone looking to add AI skills to their resume and stay ahead in a rapidly evolving industry. Complex AI concepts are made simple, with step-by-step guidance through the fundamentals.
Tech Enthusiasts
For tech-savvy individuals ready to deepen their understanding, the course covers advanced AI concepts and provides challenging hands-on projects. Gain practical skills to experiment with AI tools and apply them in real-world scenarios.
Developers
A comprehensive starting point for developers aiming to explore AI specializations. Build a strong foundation in Machine Learning, Deep Learning, and more. Learn to integrate AI into existing projects and expand your development capabilities.
Career Changers
For those looking to transition into the AI field, this course provides the essential skills and hands-on experience with AI tools, programming, and problem-solving to ensure a smooth career shift.
Listen to real people, real results
Hello, I’m Rajkamal Rajendran
My Story
My passion for Artificial Intelligence and Embedded Systems has driven me to contribute to cutting-edge research and innovation across industries. As an AI Consultant, Apple Certified Trainer (ACT), Apple Distinguished Educator (ADE), and Design Thinking Practitioner, I make complex technologies like AI, Machine Learning, and Deep Learning accessible to learners of all levels. My hands-on approach simplifies intricate concepts and encourages creative problem-solving through real-world experimentation.
Beyond teaching, I advance AI research with a focus on ethical development in industries like healthcare, IoT, and smart systems. My patents, publications, and consultancy work reflect my commitment to responsible AI innovation.
This course is your opportunity to be at the forefront of AI’s evolution, gaining the skills to make a real-world impact.
My Experience
- 2013 PhD in AI Application to Electrical Engineering
- 2018 AI Consultant
- 2020 Teaching & Research on AI, Design Thinking Practitioner
- 2022 ACT, Principal Architect, iOS app development - ML models
- 2024 ADE, Practising AI
Our mentors
Anitha Karthi
AI Consultant | Corporate Trainer
She is a seasoned expert in Artificial Intelligence and Embedded Systems with over 20 years of experience spanning academic research and industry. Specializing in making AI and Machine Learning accessible, she excels at simplifying complex concepts for diverse audiences. Known for her leadership.
Sundara Raman Narayanan
Data Science Leader
With 19 years of experience in core banking and expertise in AI, machine learning, and data science, he serves as Head of Machine Learning Engineering at Applied Data Finance. He holds advanced degrees in business analytics and IT, having worked with leading organizations like Crayon Data and TCS.
Paul T Sheeba
ACT | ADE | Principal Architect
She is a passionate educator practising AI, Machine Learning, Data Science, and iOS app development. She specializes in simplifying complex AI concepts and guiding from ideation to implementation, with a strong focus on AI-driven solutions and real-world applications.
Batch Opens
Starting
Jan 25, 2025
Duration
06 months
Early bird discount
10% off - register on before Jan 22, 2025
Mode
Instructor Led Online Training
Weekends
Saturday & Sunday
Timing
9:00 AM to 11:30 AM
Step 1
Get More Info
+91 98415 57655
training@vyoam.in
Step 2
Payment
UPI ID: vyoamaisolutions@ybl
- Email: vyoamtech@gmail.com
Step 3
Enrollment form
Find the answers to your questions here
What will be the professional outcome of learning of AI modules?
Simple, you can become a data scientist. Of course, it comes only with practice and perseverance. The most important outcome is that we will put you in a structured learning path wherein even after completion of course, you can keep learning and building your profile without any confusion like you are in now.
How will mentorship contribute to the learning experience in the course?
Mentorship will include – giving access to end to end models built already for reference. Helping students to build more projects. We will have 1 or 2 group mentorship sessions every week. The outcome is build a profile for you..
What foundational knowledge or skills are required for this course? Do learners need to meet any specific criteria before enrolling?
Good analytical skills and knack for problem-solving, creativity coupled with commitment is prerequisite. Also, some exposure to coding is expected. You need not write an object-oriented program demonstrating inheritance but if you can write a ‘for’ loop, we can take you from there.
What can I learn with AI course to achieve my career goal?
There are AI courses available for a large number of tools and wide-spanning fields. You’ll be able to learn how to use individual tools, and how to apply AI to your own workflows. Some courses can even teach you how to start building your own AI using APIs and programming languages such as Python.
How hard is it to learn AI with the availability of many tools?
Learning AI doesn’t have to be hard! After all, one of the biggest aspects of AI is about improving quality of life and saving us valuable time! AI courses vary widely depending on the skills you’re looking to learn. You can find some very beginner-friendly courses for specific tools, such as ChatGPT and Midjourney. If you’re looking to learn how to develop and build your own AI, that may take a little more patience and perseverance. If you’re just starting out, we recommend picking one of the beginner courses for an AI tool.
How do I reach perfect position in the emerging AI field?
AI is accessible to just about anyone. There are a large number of free AI tools out there which you can practice & play with to your hearts content, this is a good way to get started. Since AI is always improving, you should never feel ‘behind’, as even the best experts in the field have to keep up with the changes every month! Having a basic knowledge of computing and the web will help, but if you’re curious enough to be on this page and reading this, you’re in a perfect position already!
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