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Artificial Intelligence Training Course in Gurgaon
Become a certified Artificial Intelligence expert with this course.
2000+ Ratings
3000+ Happy Learners
Artificial Intelligence Videos
Skills Covered in Artificial Intelligence
Convolutional Neural Networks
Support Vector Machines
Natural Language Processing
Decision Tree Algorithms
Random Forest Models
Feature Engineering Techniques
Text Classification Methods
Neural Network Architecture
Predictive Model Building
Data Preprocessing Techniques
Model Performance Evaluation
Clustering Algorithm Implementation
Regression Analysis Methods
Sentiment Analysis Applications
Artificial Intelligence Training Key Features
Industry-recognised certification on course completion
100% refund on enrolment fee (minus admin charges) if unsatisfied
Lifetime access to self-paced learning content
60+ hours of hands-on, project-based training
Hands-on exposure to Python, TensorFlow, and Keras
Real-world case studies and live projects
Expert mentors with industry experience
Dedicated placement assistance and interview support
Classroom and online training modes available
Our Alumni Working in Artificial Intelligence
Artificial Intelligence Course Reviews
Debashis guru
Associate Software Engineer
All the basics will get cleared with practical session, where command line is also been taught to us with a very friendly environment. Doubt solving is also done with good examples.
Maqsood Ali
Associate Software Engineer
This is the institute for learning the courses properly. You will get the full knowledge about the courses. The way of teaching is best.Thank you apponix
Rajendra Kumar
Associate Software Engineer
Apponix technology is a well-maintained sector where you can do your internship. Advanced staff, teaching style is very good. Not only knowledge gain but you will also get best experience.
Rakshita Yadalli
Software Engineer
I went to Apponix for Artificial Intelligence training, it was really good and wonderful. Trainer was highly hands on and the entire session was hands on. I would strongly recommend freshers and also experienced candidates to take this course at Apponix. Thanks a lot to Apponix team.
Sakshi Mishra
Software Engineer
Excellent training facility. Trainer was having depth knowledge about his subject. Really very good institute for Artificial Intelligence Course with best lab facility and good infrastructure. They provide real time training and placement assistance which is very good.
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Available Training Options
Class room Training
- Interactive Classroom Training Sessions
- 60+ hours of Practical Learning
- Guaranteed 5 Interview Arrangements
- Excellent Classroom Infrastructure
- Assured Job Placement
- Delivered by Working Professionals
Online Training
- Interactive Classroom Training Sessions
- 60+ hours of Practical Learning
- Guaranteed 5 Interview Arrangements
- Excellent Classroom Infrastructure
- Assured Job Placement
- Delivered by Working Professionals
Artificial Intelligence Training Syllabus
Pre-requisites
This course is meant for professionals who want to upgrade their careers and become AI engineers.
Working professionals with job roles like –
- Analytics managers
- Information architects
Analytics professionals can also also enroll in this course. Applications from graduates with technical backgrounds are also welcome. As for prerequisites for this course, there are none.
Artificial Intelligence Course Syllabus
Artificial Intelligence
Module 1 - Decoding Artificial Intelligence
- Decoding Artificial Intelligence
- Meaning, Scope, and Stages Of Artificial Intelligence
- Three Stages of Artificial Intelligence
- Applications of Artificial Intelligence
- Image Recognition
- Applications of Artificial Intelligence - Examples
- Effects of Artificial Intelligence on Society
- Supervises Learning for Telemedicine
- Solves Complex Social Problems
- Benefits Multiple Industries
- Key Takeaways
Module 2 - Python for AI
- Python Basics and Data Types
- Working with Lists, Tuples, and Dictionaries
- Control Flow: Loops and Conditional Statements
- Functions and Reusable Code Blocks
- Introduction to Jupyter Notebook
- Key Python Libraries: NumPy, Pandas, Matplotlib, Scikit-learn
- Key Takeaways
Module 3 - Fundamentals of Machine Learning and Deep Learning
- Fundamentals Of Machine Learning and Deep Learning
- Meaning of Machine Learning
- Relationship between Machine Learning and Statistical Analysis
- Process of Machine Learning
- Types of Machine Learning
- Meaning of Unsupervised Learning
- Meaning of Semi-supervised Learning
- Algorithms of Machine Learning
- Regression
- Naive Bayes
- Naive Bayes Classification
- Machine Learning Algorithms
- Deep Learning
- Artificial Neural Network Definition
- Definition of Perceptron
- Online and Batch Learning
- Key Takeaways
Module 4 - Statistics and Probability for AI
- Central Tendency: Mean, Median, Mode
- Understanding Data Distribution and Skewness
- Probability Basics and Applications in AI
- Standard Deviation and Variance
- Bias-Variance Tradeoff: Underfitting and Overfitting
- Outlier Detection and Treatment
- Correlation and Its Role in Feature Selection
- Key Takeaways
Module 5 - Machine Learning Workflow
- Learning Objective
- Machine Learning Workflow
- Get more data
- Ask a Sharp Question
- Add Data to the Table
- Check for Quality
- Transform Features
- Answer the Questions
- Use the Answer
- Key Takeaways
Module 6 - Core Machine Learning Algorithms
- Linear and Logistic Regression
- Support Vector Machines (SVM) and Kernels
- K-Nearest Neighbours (KNN)
- Naive Bayes Classification
- Decision Trees and Random Forest
- K-Means and Hierarchical Clustering
- Choosing the Right Algorithm for a Problem
- Key Takeaways
Module 7 - Performance Metrics
- Performance Metrics
- Need For Performance Metrics
- Key Methods Of Performance Metrics
- Confusion Matrix Example
- Terms Of Confusion Matrix
- Minimize False Cases
- Minimize False Positive Example
- Accuracy
- Precision
- Recall Or Sensitivity
- Specificity
- F1 Score
- Key Takeaways
Module 8 - Deep Learning Architectures
- Artificial Neural Networks (ANN): Structure and Working
- Convolutional Neural Networks (CNN) for Image Recognition
- Recurrent Neural Networks (RNN) for Sequential Data
- Introduction to TensorFlow and Keras
- Building and Training Your First Neural Network
- Key Takeaways
Module 9 - Natural Language Processing (NLP)
- Text Pre-processing and Noise Removal
- Tokenisation, Stemming, and Lemmatisation
- Feature Engineering: TF-IDF and Word Embeddings
- Named Entity Recognition and Part-of-Speech Tagging
- Text Classification and Sentiment Analysis
- Key Takeaways
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- He is a working professional and has over a decade’s worth of experience in Block chain technology
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Overview of Artificial Intelligence Training Course
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Benefits of learning Artificial Intelligence
- By taking our Artificial Intelligence certification course, you will gain a strong understanding of AI concepts and how to implement them in real-world scenarios. The benefits of our AI certification course include:
- Increased job opportunities in the growing field of AI
- Ability to build and deploy AI applications in various industries
- Strong foundation in machine learning, natural language processing, and computer vision
- Hands-on training and real-world projects to enhance your skills
- Guidance from experienced trainers who are experts in the field of AI.
Related job roles
- Business Intelligence Developer
- AI Engineer
- Machine Learning Engineer
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