Artificial Intelligence Training/Course by Experts
Our Training Process
Artificial Intelligence - Syllabus, Fees & Duration
Module 1: Introduction to Data Science
- What is Data Science?
- What is Machine Learning?
- What is Deep Learning?
- What is AI?
- Data Analytics & it’s types
Module 2: Introduction to Python
- What is Python?
- Why Python?
- Installing Python
- Python IDEs
Module 3: Python Basics
- Python Basic Data types
- Lists
- Slicing
- IF statements
- Loops
- Dictionaries
- Tuples
- Functions
- Array
- Selection by position & Labels
Module 4: Python Packages
- Pandas
- Numpy
- Sci-kit Learn
- Mat-plot library
Module 5: Importing Data
- Reading CSV files
- Saving in Python data
- Loading Python data objects
- Writing data to csv file
Module 6: Manipulating Data
- Selecting rows/observations
- Rounding Number
- Selecting columns/fields
- Merging data
- Data aggregation
- Data munging techniques
Module 7: Statistics Basics
- Central Tendency
- Probability Basics
- Standard Deviation
- Bias variance Trade off
- Distance metrics
- Outlier analysis
- Missing Value treatment
- Correlation
Module 8: Error Metrics
- Classification
- Regression
Module 9: Machine Learning
- Supervised Learning
- Linear Regression
- Logistic regression
Module 10: Unsupervised Learning
- K-Means
- K-Means ++
- Hierarchical Clustering
Module 11: SVM
- Support Vectors
- Hyperplanes
- 2-D Case
- Linear Hyperplane
Module 12: SVM Kernel
- Linear
- Radial
- polynomial
Module 13: Other Machine Learning algorithms
- K – Nearest Neighbour
- Naïve Bayes Classifier
- Decision Tree – CART
- Decision Tree – C50
- Random Forest
Module 14: ARTIFICIAL INTELLIGENCE
- Perceptron
- Multi-Layer perceptron
- Markov Decision Process
- Logical Agent & First Order Logic
- AL Applications
Module 15: Deep Learning Algorithms
- CNN – Convolutional Neural Network
- RNN – Recurrent Neural Network
- ANN – Artificial Neural Network
Module 16: Introduction to NLP
- Text Pre-processing
- Noise Removal
- Lexicon Normalization
- Lemmatization
- Stemming
- Object Standardization
Module 17: Text to Features
- Syntactical Parsing
- Dependency Grammar
- Part of Speech Tagging
- Entity Parsing
- Named Entity Recognition
- Topic Modelling
- N-Grams
- TF – IDF
- Frequency / Density Features
- Word Embedding’s
Module 18: Tasks of NLP
- Text Classification
- Text Matching
- Levenshtein Distance
- Phonetic Matching
- Flexible String Matching
- Since 2001, Making IT Experts by Experts
- Duration: 60 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsNEAR.in
- Training/Internship Certificate
- Web Development Courses in Al Farwaniyah
- Mobile App Develpment Courses in Al Farwaniyah
- Website Design Courses in Al Farwaniyah
- Networking and Security Courses in Al Farwaniyah
- Digital Marketing (SEO) Courses in Al Farwaniyah
- Graphics Training Courses in Al Farwaniyah
- Cloud Computing Courses in Al Farwaniyah
- Mean Stack Development Courses in Al Farwaniyah
- Python Full Packages Courses in Al Farwaniyah
- Animation & Video Editing Courses in Al Farwaniyah
- Mern Stack Development Courses in Al Farwaniyah
Course Highlights
Featured Courses
Learn how to create efficient AI, self-sustaining systems, cutting-edge AI models, Deep Q-Learning, A3C, and much more.
. Artificial intelligence (AI) is the previously inconceivable ability of a computer-controlled robot to do tasks that would otherwise need human intelligence. Data Analytics is the pre-processing activity of AI.
AI uses many algorithms to method knowledge, generate data-driven judgments, and complete tasks in a manner comparable to that of a person. We are here to help you from the beginning of the course until the very conclusion, including resume-building advice and interview recommendations. The ultimate goal of AI is to create machines that can learn, plan, and solve problems on their own. Artificial intelligence is an arena of training that looks into how intelligent human behavior can be replicated on a machine. Computers, on the other hand, will avoid making these errors if they are correctly programmed. Deep Learning is at the heart of AI, which might be a basic software development capability.
