Course Overview
Foundations & Maths
Master Python, Statistics, Probability, and Exploratory Data Analysis (EDA).
Machine Learning
Learn Regression, Classification, and Model Optimization techniques.
Deep Learning & Vision
Explore Neural Networks, CNNs, Object Detection (YOLO), and Transfer Learning.
Getting Started
AI Foundations
- AI vs ML vs DL vs Data Science
- Categories of AI (Narrow, General, Applied)
- Elements of AI & Challenges
- Industry Case Studies
Outcome: Clear mental modal of AI ecosystem
Google Colab & Environment
- Introduction to Google Colab
- GPU vs CPU usage
- Folder structure & Importing datasets
- Python execution model
Outcome: Comfortable working environment
Python & Data Analysis
Modules & Libraries
- NumPy: Arrays, Reshaping, Math operations
- Statistics: Mean, Median, SD, Variance
- Probability: Binomial, Poisson, Normal Distributions
- Utility Libs: Random, OS, Time
Outcome: Mathematical confidence form ML
Exploratory Data Analysis
- Univariate, Bivariate & Multivariate Analysis
- Data Cleaning: Missing values, Outliers
- Visualization with Matplotlib/Seaborn
- Loading external datasets
Mini Project: Dataset analysis & visualization report
Machine Learning
Linear Regression
- Covariance & Correlation
- Residuals & Mean Squared Error (MSE)
- Hands-on: Model fine-tuning
Mini Project: Car price prediction
Classification Models
- Decision Trees, Random Forest, KNN
- Support Vector Machines & Logistic Regression
- Accuracy Metrics: Precision, Recall, F1
- Multi-model comparison on real datasets
Mini Project: Classifier comparison
Computer Vision
Image Processing
- OpenCV Basics: Reading & Writing
- Masking, Smoothing, Blurring
- Thresholding & Contours
- Drawing operations
Mini Project: License plate Detection
Image-Based ML
- Feature Extraction: HOG, Haralick Textures
- Face Detection (Haar Cascades)
- Face Recognition (LBP)
- Numerical Data Classification
Mini Project: Face Emotion Recognition
Deep Learning
Neural Networks & CNN
- Unsupervised: K-Means, DBSCAN
- NN: Activation Functions, Backpropagation
- CNN: Convolution & Pooling Layers
- Transfer Learning Implementation
Mini Project: Plant Disease Classification
Advanced Concepts
- Object Detection Overview
- YOLO Architecture & Implementation
- GAN (Generative Adversarial Networks) Basics
- Deployment-ready notebook creation
Mini Project: Helemet Detection (custom object)
Project Showcase
Career Services At UPVION
Get ready for your dream job! Attend comprehensive industry readiness training with Career Services.
Communication Skills
Interview Preparation Workshop
1:1 Career Mentoring
Project Preparation
Profile Enhancement
Resume Building
Mock Interviews
Placement Support
Online & Offline Batch Flexiblity
Get live training and interaction with trainers through online and offline batch flexibility
Industry-Relevant & Updated Syllabus
Learn the industry's latest tools, techniques & trends.
360 Degree Knowledge Building
Develop practical skills through real-world projects & assignments
1:1 Dedicated Mentorship
Personalized learning experience from experienced industry professionals.