3-MONTH INTENSIVE · TRIVANDRUM, KERALA

Master Artificial Intelligence.

A complete journey through Machine Learning, Deep Learning, and Neural Networks — taught by industry experts at Kerala's premier IT training institute. Build real models. Solve real problems. Launch a real career.

12+ Weeks Curriculum
30+ Hands-On Modules
100% Placement Support
INPUT HIDDEN DEEP OUTPUT
01 — THE PROGRAM

A complete 3-month journey from foundations to deployment.

From the mathematics of data to the architecture of neural networks — our curriculum is meticulously designed to align with current industry demands. You'll move through machine learning fundamentals, advanced deep learning frameworks like TensorFlow and Keras, and into the frontier of natural language processing and transformer models.

/ 01

Data Science & Analysis

Master the foundations — data collection, preprocessing, cleaning, feature engineering, and exploratory data analysis using Python, NumPy, Pandas and Scikit-Learn.

/ 02

Machine Learning

Supervised, unsupervised, semi-supervised and reinforcement learning. Master regression, classification, clustering, SVM, KNN, ensemble methods and tree-based algorithms.

/ 03

Deep Learning

Dive into CNNs, RNNs, MLPs and transformer architectures. Hands-on with TensorFlow, Keras and OpenCV — backpropagation, optimization, and model deployment.

/ 04

NLP & Transformers

Natural Language Processing with BERT, Word2Vec, GloVe, attention mechanisms and sequence-to-sequence models. Build the AI that understands human language.

02 — SYLLABUS

Every module. Every algorithm.

Switch between the three pillars of the program. Each track builds on the last — a deliberate progression from data fluency to deep architectures.

/ 01

Data Science & Analysis

  • Foundations of Data Science
  • Data Analysis & EDA
  • Exploratory Data Analysis
/ 02

Data Handling

  • Data Collection & Preparation
  • Data Preprocessing
  • Integration & Transformation
/ 03

Data Cleaning

  • Cleaning Techniques & Imputation
  • Handling Outliers
  • Validation & Automation
/ 04

Feature Engineering

  • Feature Scaling & Encoding
  • Dataset Balancing
  • PCA & Information Gain
/ 05

Artificial Intelligence

  • History, Types & Applications
  • Subsets of AI
  • ML vs Deep Learning
/ 06

Statistics & Probability

  • Descriptive & Inferential Statistics
  • Probability Distributions
/ 07

Python Programming

  • NumPy & SciPy
  • Scikit-Learn
  • Pandas
/ 08

Data Visualization

  • Matplotlib
  • Seaborn
/ 01

Supervised Learning

  • Linear Regression & KNN
  • Support Vector Machines
  • Ensemble & Tree-Based Algorithms
/ 02

Unsupervised Learning

  • Clustering Algorithms
  • Hierarchical Clustering
  • Apriori Algorithm
/ 03

Semi-Supervised Learning

  • Self-training & Co-training
  • Graph-based Methods
  • Semi-supervised SVMs
/ 04

Reinforcement Learning

  • Markov Decision Processes
  • Q-Learning
/ 05

Model File Formats

  • HDF5, PMML, ONNX
  • TensorFlow SavedModel, PyTorch
  • Docker for Deployment
/ 06

Implementation Phases

  • Model Development Life Cycle
  • Deployment Strategies
  • CI/CD Pipelines
/ 07

Evaluation Measures

  • Classification Metrics
  • Regression Metrics
  • Clustering Metrics
/ 01

Neural Network Foundations

  • Neural Network Terminology
  • Training & Backpropagation
  • Callback Functions
/ 02

DL Python Packages

  • TensorFlow
  • Keras
  • OpenCV
/ 03

Neural Network Layers

  • Convolution & Pooling
  • Dropout & Flatten
  • Dense & Batch Normalization
/ 04

Network Architectures

  • Multilayer Perceptron (MLP)
  • Convolutional NN (CNN)
  • Recurrent NN (RNN)
/ 05

Natural Language Processing

  • NLP Preprocessing
  • Word Embeddings
  • Word2Vec & GloVe
/ 06

Sequence-to-Sequence

  • Encoder-Decoder Architecture
  • Attention Mechanisms
  • Training & Optimization
/ 07

BERT & Transformers

  • Transformer Architecture
  • BERT Models
/ 08

Ethics & Optimization

  • Fairness & Bias
  • Hyperparameter Tuning
  • Regularization & Data Augmentation
03 — YOUR ROADMAP

From curious beginner to AI engineer.

The path is structured but flexible — designed to take you from foundational concepts to deploying production-grade AI models in just twelve weeks.

Weeks 1–3 · Foundations

Python, statistics, probability, data wrangling. Build the mathematical and programming fluency every AI engineer needs.

Weeks 4–6 · Machine Learning

Regression, classification, clustering. Train your first models on real datasets and measure them with proper evaluation metrics.

Weeks 7–9 · Deep Learning

Neural networks, CNNs for computer vision, RNNs for sequences. TensorFlow and Keras become second nature.

Weeks 10–11 · NLP & Transformers

Process language with BERT, build sequence models with attention, work with pre-trained transformers.

Week 12 · Capstone & Deployment

Build, evaluate, and deploy a portfolio-grade AI project. CI/CD, model serving with Docker, certification & placement.

04 — WHY TRINITY

Kerala's premier IT training institute — built for the AI era.

Located in the heart of Trivandrum, Trinity Technologies has earned its reputation by combining expert instruction, real-world infrastructure, and dedicated placement support.

/ 01

Expert Instructors

Industry-experienced mentors who guide you through complex AI concepts and prepare you for certification exams and real-world challenges.

/ 02

State-of-the-Art Infrastructure

Latest AI tools, high-performance computing labs, and the software stack you'll use in industry — all available throughout your training.

/ 03

Comprehensive Curriculum

From neural networks to AI ethics and governance — every module is aligned with current industry demands and includes capstone projects.

/ 04

Hands-On Lab Experience

Extensive practical labs where you build live AI models and deploy them in simulated real-world environments — not just slides.

/ 05

Regular Assessments

Mock exams and detailed feedback help you steadily improve, ensuring you're confident and certification-ready by the program's end.

/ 06

Placement Support

Resume building, interview prep, and an active placement cell working with leading tech companies to secure your AI career.

05 — QUESTIONS

Frequently asked.

Everything you need to know before you enroll. Still curious? Reach out — we love talking about AI.

What is AI training?

AI training involves learning the concepts, tools, and techniques used to develop and implement Artificial Intelligence systems — including machine learning, neural networks, and data analysis.

Why choose AI training in Trivandrum?

Trivandrum is home to several leading IT and technology institutes, making it an ideal location for high-quality AI training with access to experienced professionals and cutting-edge resources.

What are the prerequisites?

A basic understanding of programming and mathematics is recommended. However, introductory modules are available for those new to the field.

What topics are covered?

Topics include machine learning, neural networks, deep learning, natural language processing, AI ethics, and hands-on capstone projects.

How long does the course take?

The comprehensive AI training program at Trinity Technologies typically takes 3 months, depending on the intensity and chosen batch format.

What's the job market like after certification?

AI professionals are in high demand across technology, healthcare, finance, and manufacturing — with roles such as AI engineer, data scientist, and machine learning specialist.

06 — BEGIN

Your AI career starts here.

Visit our Trivandrum campus, talk to our team, and step into one of the most in-demand fields of our generation.

Call: +91 94473 87064 Email Us