Master Machine Learning, Deep Learning & Advanced Analytics
About This Program
The Data Science & Artificial Intelligence Training Program at Pere Technologies, Trichy is designed to develop strong analytical, statistical, and AI engineering skills using industry-standard tools — Python, R, Scikit-learn, TensorFlow, NumPy, Pandas, and Matplotlib — on real-world datasets.
This program prepares learners to analyze structured and unstructured data, build predictive machine learning models, develop AI-powered intelligent systems, implement deep learning architectures, and work with Python and R for analytics — with personalized 1-to-1 mentorship at every stage.
Whether you are a fresher, working professional, or career switcher from any background — this structured program focuses on practical implementation aligned with real industry use cases, making you model-ready and interview-confident for Data Science and AI roles in Trichy and across India.
Specializations We Teach
Choose the specialization that matches your career goal — or build end-to-end Data Science and AI expertise across the full analytics and intelligence stack.
The foundation of every data-driven organization. Learn end-to-end data science workflows — data collection, cleaning, exploratory data analysis (EDA), feature engineering, visualization, and insight generation for business decision-making.
Design and build intelligent systems capable of reasoning, learning, and autonomous decision-making. Covers AI principles, search algorithms, knowledge representation, natural language processing (NLP) basics, and AI system architecture.
The core of modern AI applications. Master supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), ensemble methods (Random Forest, XGBoost, Gradient Boosting), and model evaluation techniques.
Build and train multi-layer neural networks — Convolutional Neural Networks (CNNs) for image data, Recurrent Neural Networks (RNNs) for sequential data, backpropagation, activation functions, dropout regularization, and optimization techniques.
The most in-demand data science track globally. Use Python and its data science libraries — NumPy (numerical computing), Pandas (data manipulation), Matplotlib and Seaborn (visualization) — for complete analytics workflows on real datasets.
Build production-ready machine learning models using Python's Scikit-learn — regression, classification, clustering, feature selection, cross-validation, hyperparameter tuning, and model deployment pipelines.
Apply machine learning using R — caret and tidymodels packages, statistical learning methods, regression models, classification trees, ensemble methods, and model evaluation in R for research and analytics environments.
Data science using R's powerful ecosystem — dplyr for data wrangling, ggplot2 for advanced visualization, tidyverse for clean data pipelines, and statistical analysis for academic and industry research projects.
Google's deep learning framework — the industry standard for production AI. Learn TensorFlow model building, Keras high-level API, CNN/RNN architectures, training pipelines, model saving and deployment using TensorFlow Serving.
Build AI systems that understand and process human language. Learn text preprocessing, tokenization, sentiment analysis, named entity recognition (NER), text classification, word embeddings, and transformer models (BERT, GPT basics).
Curriculum
Statistics for data science, Python/R programming basics, NumPy, Pandas, data cleaning, exploratory data analysis (EDA), and data visualization with Matplotlib and Seaborn.
Supervised learning (regression, classification), unsupervised learning (clustering, PCA), ensemble methods (Random Forest, XGBoost), model evaluation, and cross-validation.
Feedforward neural networks, CNNs for image classification, RNNs for sequential data, backpropagation, dropout regularization, and optimization with Adam and SGD.
Building, training, and evaluating deep learning models using TensorFlow 2.x and Keras. Model saving, loading, and deployment using TensorFlow Serving and TFLite.
Text preprocessing, NLTK, spaCy, sentiment analysis, text classification, word embeddings (Word2Vec, GloVe), and introduction to transformer models.
Build end-to-end ML/AI projects on real datasets from finance, healthcare, and e-commerce. Deploy models as APIs using Flask and FastAPI.
Course Architecture
Ideal for: Complete beginners and non-IT learners
Ideal for: Learners with Python/R and statistics knowledge
Ideal for: Intermediate learners targeting AI Engineer roles
Tech Stack
PythonR ProgrammingTensorFlow
PyTorchPandas / NumPy
Jupyter Notebook
Tableau / Power BI
SQL for DataOutcomes
Career Opportunities
Average starting salary for Data Science & AI roles in India: ₹4 LPA – ₹12 LPA. AI Engineers and ML Engineers typically command higher packages than Data Analysts.
Pere Technologies Advantage
Pere Technologies is Trichy's trusted IT training and placement institute with a proven record of placing students in Data Science and AI roles at leading technology companies across India.
Every learner gets a dedicated Data Science mentor — guiding you through real datasets, reviewing your models, and preparing you for technical AI interviews at top companies.
Work on datasets from finance, healthcare, e-commerce, and social media — building ML/AI models that solve actual business problems and form a compelling project portfolio.
Resume building, data science mock interviews, case study preparation, and direct connections to 50+ hiring partners ensure you complete the program and land a data role.
Full Syllabus
Want the complete detailed syllabus?
Got Questions?
Freshers, IT professionals, working professionals, and career switchers from any background can join. Basic mathematics/statistics knowledge helps, but Python basics are taught from the start.
Basic Python or programming knowledge helps but is not required. The program begins with Python fundamentals before moving to data science libraries and machine learning.
Python is the most in-demand globally — preferred for machine learning, AI, and industry roles. R is preferred for statistical research and academic environments. Our trainers guide you to the right choice based on your career goal.
Data Analyst, Data Scientist, Machine Learning Engineer, AI Engineer, Deep Learning Engineer, NLP Engineer, Business Intelligence Analyst, and Research Analyst.
Yes. Resume building, data science mock interviews, case study preparation, and direct placement assistance are included for all Data Science and AI tracks.
Pere Technologies offers competitive course fees for the Data Science & AI program, with flexible instalment options. Contact us at +91 890 383 1590 for current pricing.