COMPUTER VISION COURSE TRAINING IN HYDERABAD

About LearnAi.co.in

LearnAI.co.in training institute offers comprehensive Computer Vision courses designed to cater to individuals of all skill levels, from beginners to intermediates and experts. Our courses are structured with a focus on hands-on learning, ensuring that even beginners can grasp the fundamentals. Intermediate learners benefit from in-depth modules, sharpening their skills in image processing and object detection. For experts, we offer advanced topics like neural networks and deep learning to fine-tune their expertise. With our practical approach, learners at every level gain the knowledge and confidence needed to excel in Computer Vision. Join LearnAI.co.in and unlock your potential in this exciting field!

Upcoming Batches

CourseBranchTraining TypeWeekDay
Computer VisionDilsukhnagarHybrid1stWednesday
Computer VisionDilsukhnagarHybrid2ndMonday
Computer VisionDilsukhnagarHybrid3rdWednesday
Computer VisionDilsukhnagarHybrid4thMonday

What is Computer Vision?

Computer Vision is a technology that enables computers to understand and interpret visual information from the world, just like our own eyes and brain. It helps machines recognize objects, patterns, and even movements, making it a crucial part of fields like self-driving cars and facial recognition systems.

Why to learn Computer Vision?

Learning computer vision is a smart career move due to its immense potential in today's job market. As industries increasingly adopt this technology for applications like autonomous vehicles, healthcare diagnostics, and augmented reality, mastering computer vision can open doors to high-demand and well-paying positions in fields that are shaping the future.

Who can Pursue Computer Vision?

  • Any Degree pursuing or Graduated,
  • Bachelor’s, Master’s, PhD, and
  • Anyone interested in course
Enroll to Course Now

COURSE CURRICULUM

Python

  • Introduction
  • Installation
  • Fundamental of Python
  • Variables
  • Comments
  • Print Statement
  • Operators
  • Mutable Data Types
  • Data Types
  • Special Data Types
  • Conditions
  • Loops
  • Functions
  • Break, Continue and Pass Statements
  • String Object and working
  • List
  • Tuple
  • Set
  • Dictionaries
  • Map
  • Reduce
  • Filter
  • Classes
  • Objects
  • Inheritance
  • Multiple Inheritance
  • Modules
  • Error Handling

Data Visualization

  • Matplotlib
  • Seaborn
  • Plotly
  • Cuflinks
  • Bokesh

Libraries

  • Numpy
  • Pandas
  • Random
  • Math
  • Scipy
  • sklearn
  • Keras
  • Tensorflow
  • OpenCV
  • NLTK
  • Spacy
  • Lot more…

Tableau

  • Introduction to Data Visualization
  • Introduction to Tableau
  • Basics charts and dashboards
  • Special Char Types
  • Dashboard design and principles
  • Connections with servers
  • Local file access
  • Hands on experience with worksheet

Web Scraping

  • Url
  • Beautiful Soup

Data base

  • SQL
  • MongoDB

Statistics

  • Basics of Statistics
  • Descriptive Statistics
  • Inferential Statistics
  • Qualitative Analysis
  • Quantitative Analysis
  • Hypothesis Testing
  • Data Distribution
  • Probability Distribution
  • Normal Distribution
  • Poison Distribution
  • Outlier Detection
  • Other Statistical Fundamentals

Machine Learning

  • Supervised Learning
  • Unsupervised Learning
  • Semi Supervised Learning
  • Reinforcement Learning

Supervised Learning

  1. Regression Models
  2. Classification Models

Regression Models

  • Introduction to Regression Models
  • Linear Models
  • Linear Regression
  • Multiple Regression
  • Ordinary Least Square Method
  • Non-Linear Models
  • Support Vector Regressor
  • Random Forest Regressor
  • Decision Tree

Evaluation Metrics for Regression Models

  • R-Square
  • Adjusted R Square
  • Mean Square Error
  • Root Mean Square Error
  • Mean Absolute Error

Classification Models

  • Introduction to Classification Models
  • Logistics Regression
  • Naïve Bayes
  • Support Vector Classifier
  • K-NN Classifier
  • Decision Tree Classifier
  • Random Forest Classifier

Evaluation Metrics for Classification Models

  • Accuracy
  • Precision
  • Recall
  • F1 Score
  • ROC Curve

Unsupervised Learning

  • Introduction to Unsupervised Learning

Clustering Models

  • Introduction to Clustering Models
  • K- Mean Clustering
  • Hierarchical Clustering
  • High Dimensional Clustering

Dimension Reduction

  • Principal Component Analysis (PCA) Reinforcement Learning

Reinforcement Learning

  • Introduction to Reinforcement Learning

Featurization, Model Selection & Tuning

  • Feature Extraction
  • Model Defects & Evaluation Metrics
  • Model Selection and Tuning
  • Comparison of machine learning models

Neural Networks

  • Introduction to Deep Learning
  • Fundamental of Neural Networks
  • TensorFlow and Keras
  • Artificial Neural Networks (ANN)
  • Convolution Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
  • Evaluation of Deep Learning
  • Neural Networks Basics
  • Gradient Descent
  • Introduction to Perceptron & Neural Networks
  • Batch Normalization
  • Activation and Loss Functions
  • Hyper parameter tuning
  • SoftMax
  • Deep Neural Networks
  • Weights initialization

Image Pre-processing

  • Computer Vision
  • Open CV
  • Noise Detection
  • Noise Reduce
  • Low Pass Filters
  • Forward Propagation
  • Backward Propagation
  • Pooling & Padding

Natural Language Processing

  • Introduction to NLP
  • Corpus
  • Natural Language Understanding (NLU)
  • Natural Language Generator (NLG)
  • Tokenization (Word, Sentence, Blank, RegEx)
  • Frequency Distribution
  • Filtering
  • Stemming
  • Lemmatization
  • Stop Words
  • Regular Expressions
  • POS Tagging
  • Syntax Tree
  • Chunking
  • Lemmas
  • Hypernyms
  • Hyponyms
  • Synonyms
  • Antonyms
  • Distance Between words
  • Wordnet
  • Name Entity Recognition
  • Bag of words or Document Matrix
  • Count Vectorization
  • Term Frequency
  • Inverse Document Frequency
  • Sentimental Analysis

Job Roles

  • Computer Vision Engineer
  • Machine Learning Engineer
  • Data Scientist
  • Robotics Engineer
  • Image Processing Specialist
  • AI Research Scientist
  • Augmented Reality Developer
  • Biomedical Image Analyst
  • Natural Language Processing Engineer
  • Product Manager (Computer Vision)

Components of Computer Vision

  • Cameras and Sensors
  • Computing Hardware
  • Software Frameworks
  • Machine Learning Models
  • Image Annotation Tools
  • Data Storage Solutions
  • Data Preprocessing Tools
  • Deep Learning Frameworks
  • Development Environments
  • 3D Modeling Software
  • Augmented Reality (AR) Devices
  • LiDAR Sensors
  • Robotics Hardware
  • Cloud Services
  • Version Control Systems
  • Data Labeling Services
  • Performance Metrics Tools
  • Testing Equipment
  • Communication and Collaboration Tools
  • Security Measures

What We Offer

24/7 Portal Access
Domain Expertise Trainers
Industrial Standard Course Structure
Job Oriented Programs
Recording Sessions
Assignments on Real time Scenarios
Job Support
Resume Preparations
Internships
Job Assistance
Working on Real Time Projects
Course Completion Certifications

We Provide Higher Quality Services

AND YOU’LL GET SOLUTIONS FOR EVERYTHING
Best Artificial Intelligence Training in Hyderabad with 100% placement Assistance. Learn Data Science with Python, Data Analysis, Artificial Intelligence, Machine Learning, Deep Learning, NLP, Statistics and Tableau.

Branches

KPHBSR NagarSecunderabad
Phone: +91 9390023585
Email: info@learnai.co.in

Head Office

Address: 1st Floor, Rajadhani Theatre Complex, Pillar Number 1546, above Siri Mobiles, Dilsukhnagar, Hyderabad, Telangana 500060.
Phone: +91 9390023585
Email: info@learnai.co.in
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