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Artificial Intelligence Training in Chennai
Are you seeking exceptional AI Training? In Chennai, BITA Academy provides Artificial Intelligence Training. AI isn’t just for engineers. If you would like your business to improve its use of AI, this is the training to recommend to everyone, particularly non-technical colleagues. It teaches you to think and learn via a computer or machine. AI Programming teaches you to collect data and apply rules to complete a task.
What is Artificial Intelligence?
Artificial intelligence (AI) is a capability of a computer or a robot operated by a computer to do tasks that usually require human intelligence and insight. Although no AI can accomplish the full range of tasks an ordinary human can, some AIs can match humans in specific skills.
Importance of Learning Artificial Intelligence
The primary purpose of artificial intelligence is to train the machine to think and act appropriately. Artificial intelligence technology is only achievable in real time because of the integration of Data Science and Machine Learning. Machine Learning is a statistical technique for exploring data, and in our Artificial Intelligence Training in Chennai, you will learn the process and tricks of how machines anticipate the future.
Deep Learning is a subtype of machine learning that produces architecture known as Multi Neural Network Architecture. Deep Learning’s primary goal is to emulate the human brain, allowing machines to think like humans.
Our AI Courses in Chennai will teach you how artificial intelligence works and the skills required to use it. An artificial neural network is a type of machine learning in which interconnected units interpret data by responding to external inputs. Anyone interested in learning Artificial intelligence Training in Chennai should focus on the following subjects.
- Machine Learning
- Neural Network
- Cognitive Computing
- Deep Learning
- Natural Language Processing (NLP)
Syllabus for Artificial Intelligence
Module 1: Introduction to Data Science
- What is Data Science?
- What is Machine Learning?
- Do you know what is Deep Learning?
- What is AI?
- Data Analytics & its types
Module 2: Introduction to Python
- What is Python?
- Why Python?
- How to install Python?
- Python IDEs
- Jupyter Notebook Overview
Module 3: Python Basics
- Python Basic Data types
- Lists
- Slicing
- IF statements
- Loops
- Dictionaries
- Tuples
- Functions
- Array
- Selection by position and Labels
Module 4: Python Packages
- Pandas
- Numpy
- Sci-kit Learn
- Mat-plot library
Module 5: Import Data
- How to read CSV files?
- How to save in Python data?
- Do you know how to load Python data objects?
- How to write data to csv file?
Module 6: Manipulate Data
- How to select rows/observations?
- Do you know to round Number?
- How to select columns/fields?
- Merge data
- Deep Dive on Data aggregation
- Deep Dive on Data munging techniques
Module 7: Statistics Basics
- Central Tendency
- Mean
- Median
- Mode
- Deep Dive on Skewness
- Normal Distribution
- What does it mean by probability?
- Types of Probability
- ODDS Ratio
- Standard Deviation
- Data deviation & distribution
- Variance
- Bias variance Trade off
- What is Underfitting?
- What is Overfitting?
- Distance metrics
- Deep Dive on Euclidean Distance
- Deep Dive on Manhattan Distance
- Outlier analysis
- What is an Outlier?
- InterQuartile Range
- Box and whisker plot
- Upper Whisker
- Lower Whisker
- Scatter plot
- Cook’s Distance
- Missing Value treatment
- What is a NA?
- What do you know about Central Imputation?
- Deep Dive on KNN imputation
- What do you know about Dummification?
- Correlation
- Deep Dive on Pearson correlation
- Positive and Negative correlation
Module 8: Error Metrics
- Classification
- Confusion Matrix
- Precision
- Recall
- Specificity
- F1 Score
- Regression
- MSE
- RMSE
- MAPE
Module 9: Machine Learning
- Supervised Learning
- Deep Dive on Linear Regression
- What do you know about Linear Equation?
- Slope
- Intercept
- R square value
- Logistic regression
- ODDS ratio
- How to find Probability of success?
- How to find Probability of failure Bias Variance Tradeoff?
- ROC curve
- Deep Dive on Bias Variance Tradeoff
Module 10: Unsupervised Learning
- K-Means
- K-Means ++
- Deep Dive on Hierarchical Clustering
Module 10: SVM
- Support Vectors
- Hyperplanes
- 2-D Case
- Deep Dive on Linear Hyperplane
- What do you know about SVM Kernel?
- Linear
- Radial
- What do you know about Polynomial?
Module 11: Other Machine Learning algorithms
- K – Nearest Neighbour
- Naïve Bayes Classifier
- Decision Tree – CART
- Decision Tree – C50
- Random Forest
Module 12: Artificial Intelligence
- AI Introduction
- Perceptron
- Multi-Layer perceptron
- Markov Decision Process
- Logical Agent and First Order Logic
- Look Around AI Applications
Module 13: Deep Learning Algorithms
- CNN – Convolutional Neural Network
- RNN – Recurrent Neural Network
- ANN – Artificial Neural Network
Module 14: Natural Language Processing
- NLP – An Overview
- Text Pre-processing
- Noise Removal
- Lexicon Normalization
- Lemmatization
- Stemming
- Object Standardization
Module 15: Text to Features (Feature Engineering)
- Deep Dive on Syntactical Parsing
- Dependency Grammar
- Part of Speech Tagging
- What do you know about Entity Parsing?
- Named Entity Recognition
- Topic Modelling
- N-Grams
- TF – IDF
- Frequency / Density Features
Module 16: NLP Task
- Text Classification
- Text Matching
- What do you know about Levenshtein Distance?
- Deep Dive on Phonetic Matching
- What do you know about Flexible String Matching?
AI Certification Training
Companies and organizations are looking for qualified candidates to secure high-paying positions on the cutting edge of artificial intelligence innovation. Programs, certificates of authenticity, and qualifications can help you obtain experience. Taking a course or earning a certification program is an excellent way to advance your career and demonstrate your dedication to learning more about artificial intelligence. Many courses are introductory and entry-level, depending on where you are in your AI journey, while other intermediate alternatives provide specialized expertise in a specific AI subset. These job prospects will help you better prepare for specific positions and admission to AI.
- Certified Artificial Intelligence Engineer
- IBM Applied AI Professional Certificate
- IBM AI Engineering Professional Certificate
AI consists of algorithms responsible for making a decision or a prediction about the next required tasks.
The data is analyzed by those algorithms, and as a result, it is represented by the proper and quick decisions.
DEEP LEARNING AND MACHINE LEARNING: EXPLAINING THE TERMINOLOGY
What do we mean under the term AI today
It is known that Artificial Intelligence is the set of algorithms that include just code and math and their task is to make the decision concerning the data.
So AI is the general term that can be used for any program that can perform smartly.
When one talks about new developments in AI then the terms machine learning, deep learning also find their special mentions and are regularly utilized interchangeably as a result AI is frequently connected with intelligent machines.
Limited AI is less demanding and easier to be tasked for restricted capacities.
It can show a measure of intelligence, however, it is limited done particular idea also execution in-so-far as programmers execute algorithms for a characterized work what’s more reason for existing incorporating misfortune function, goal function, what’s more, lapse capacity.
This is an iterative process and leads to deep learning.
In this way instead of depleting composing programming framework routines for particular directions to finish a particular task, machine learning in might make An way for “training” a manager in a request that it will figure out how.
Deep alludes to the amount about simulated neural networks that type and only a calculation and the layers might be orchestrated On An progression with simpler characteristics joining together to structure progressively additional intricate features.
Today, many online course creators use technology such as augmented reality and virtual reality to make online learning courses more immersive, meaningful, real-time and exciting.
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