AI ML

In today’s data-driven world, AI and Machine Learning are transforming every industry — from healthcare and finance to retail and cybersecurity. At Aazain Infotech, our AI/ML training programs are designed to equip learners with the foundational knowledge, practical tools, and advanced techniques needed to build intelligent systems and data models that solve real-world problems.

4.3

12+

Course Lessons

13+

Certified Training

What you'll learn

Level 1

AI / ML– Fundamentals (Beginner)

AI/ML Level 1 – Fundamentals (Beginner)

Top AI / ML training topics that are essential for a basic (beginner-level) AI / ML training program
This foundational course introduces learners to the world of Artificial Intelligence and Machine Learning through real-world examples, essential concepts, and beginner-friendly tools. Students gain a broad understanding of how machines learn, how data is processed, and how AI is transforming industries.
  • Students and fresh graduates
  • Non-technical professionals exploring AI/ML
  • IT beginners and support staff
  • Early-career developers or analysts
  • Understand the differences between AI, ML, and Data Science
  • Learn data types, variables, logic, and decision structures
  • Introduction to Python programming
  • Basics of data wrangling and visualization
  • Exposure to AI applications in daily life
  • Write simple Python programs for data analysis
  • Perform basic data cleaning and plotting
  • Understand AI terminology: supervised, unsupervised learning, classification
  • Describe use cases in finance, healthcare, security, etc.
  • Introduction to AI, ML, and Data Science
  • Basics of Python Programming
  • Working with Data: CSV, Excel, JSON
  • Data Cleaning with Pandas
  • Visualization with Matplotlib and Seaborn
  • Introduction to Algorithms & Models
  • AI/ML in the Real World
  • Beginner Mini Project
Participants will receive the AI/ML Level 1 – Fundamentals Certificate, demonstrating foundational competence in data and AI technologies.
Level 2

AI/ML – Intermediate (Practitioner)

Mid-Level AI / ML Training Topics

For a mid-level AI / ML training program, the focus shifts from basic awareness to practical skills, risk management, and deeper technical understanding.
This level focuses on building and deploying machine learning models using industry-standard tools and methods. It emphasizes applied learning through structured datasets, algorithm selection, and performance evaluation.
  • Junior data analysts or software engineers
  • Students with basic Python and math skills
  • IT professionals aiming to pivot to AI roles
  • Learn statistical foundations required for ML
  • Explore supervised and unsupervised ML algorithms
  • Apply Scikit-learn to train and tune models
  • Understand the ML pipeline: preprocessing to evaluation
  • Perform real-world model building and analysis
  • Apply regression, classification, clustering algorithms
  • Evaluate models using confusion matrix, accuracy, precision, recall
  • Automate data transformation and feature engineering
  • Work with Jupyter notebooks and Scikit-learn
  • Apply ML to business datasets
  • Linear Algebra & Statistics for ML
  • Supervised Learning: Linear, Logistic Regression
  • Decision Trees, Random Forests, KNN
  • Unsupervised Learning: Clustering, PCA
  • Model Tuning & Evaluation
  • Working with Real-World Datasets
  • Introduction to Model Deployment
  • Capstone Project: ML Use Case
Participants will receive the AI/ML Level 2 – Practitioner Certificate, showcasing applied ML modeling proficiency.
Level 3

AI/ML– Advanced (Role-Based)

AI/ML– Advanced (Role-Based)

For a mid-level cybersecurity training program, the focus shifts from basic awareness to practical skills, risk management, and deeper technical understanding.
The advanced program is designed for professionals aiming to become AI/ML specialists or transition into data science, NLP, or AI engineering roles. The focus is on deep learning, neural networks, NLP, computer vision, and Generative AI.
  • Working professionals in AI/ML or data science
  • AI/ML Level 2 graduates
  • Developers transitioning into AI engineer roles
  • Individuals preparing for AI certifications or interviews
  • Build deep learning models using TensorFlow & Keras
  • Apply Convolutional Neural Networks (CNNs) for image classification
  • Work with LSTM, transformers, and NLP models
  • Build and fine-tune large language models (LLMs)
  • Explore ethical AI, responsible AI, and bias reduction
  • Implement DNNs, CNNs, and RNNs for different datasets
  • Train AI systems for text, speech, and image processing
  • Build end-to-end AI pipelines with deployment options
  • Apply Prompt Engineering and work with Generative AI
  • Create AI-driven projects for business/enterprise scenarios
  • Deep Learning Overview & Keras/TensorFlow Basics
  • Neural Networks (Feedforward, Backpropagation)
  • CNNs for Image Recognition
  • RNNs, LSTMs for Time-Series & NLP
  • Transformers & BERT Models
  • Prompt Engineering & Generative AI
  • Responsible AI & Bias Mitigation
  • Final Project & Interview Prep
Participants will receive the AI/ML Level 3 – Advanced Role-Based Certificate, validating high-end skills for job roles like AI Engineer, Data Scientist, or ML Researcher.