Live
Artificial
Intelligence
Live Mentorship by Experts | Course Completion Certificate | Internship Certificate
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Course overview
his Artificial Intelligence with Machine Learning course offers a comprehensive dive into Python programming, machine learning algorithms, data visualization, and neural networks. Designed for beginners and professionals alike, it provides hands-on experience with AI tools and techniques, equipping you with practical skills to apply in real-world projects.
COURSE STRUCTURE
Introduction to Python for AI
- Installing Anaconda
- Jupyter Notebook Basics
- Python Data Types
- Lists, Tuples, Sets, Dictionaries
- File Handling in Python
Loops and Conditionals in Python
- If, elif, else statements
- For loops
- While loops
- Numpy hands-on
- Pandas hands-on
Data Visualization and Statistical Thinking
- Data Exploration and Visualization
- Matplotlib & Seaborn hands-on
- Central Tendency Measures
- Dispersion Measures
- Hands-on Statistical Analysis
Supervised and Unsupervised Learning
- Classification and Regression
- Linear Regression
- Logistic Regression
- Hands-on Model Fine-tuning
- Metrics for Model Evaluation
Data Preprocessing for Machine Learning
- Standardizing Data
- Handling Missing Values
- Outlier Detection
- Feature Scaling
- Exploratory Data Analysis
Neural Networks and Deep Learning
- Neural Network Fundamentals
- Creating Models
- Project on Data Science
- Hands-on NLP with NLTK
- Neural Networks for AI
Natural Language Processing (NLP)
- NLTK and Spacy
- Text Data Preprocessing
- Gensim and FastText
- Sentiment Analysis
- NLP for AI Applications
Tree-Based Models
- Decision Trees
- Random Forest
- Bagging & Boosting
- Hands-on with Tree-based Classifiers
- Regression Trees
Generative AI and Advanced Topics
- Introduction to Generative AI
- Models like ChatGPT, Dall-E
- Use Cases for Generative AI
- Hands-on with AI Generation
- Huggingface Models
Learning Objectives
- Understand the fundamentals of AI and machine learning.
- Learn Python programming for AI applications.
- Master supervised and unsupervised learning models.
- Gain expertise in data preprocessing and visualization.
- Explore NLP and Generative AI models in real-world use cases.
Learning Methods
- Presentations & Lectures
- Hands-On, Project-Based Learning
- Live Mentorship Sessions
- Self-Paced Learning & Recorded Lectures
Learning Outcome
By completing this course, you'll be able to confidently implement AI and ML algorithms, build and optimize machine learning models, and create neural networks. You will also acquire skills in handling large datasets, performing data analysis, and using generative AI techniques in applications.
How to Enroll Program
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Elevate your skills with hands-on experience, 12+ live projects, and mentorship from industry-leading experts in the top 2% of their field. Our tailored plans cater to your unique needs, allowing you to transform your practical knowledge into real-world expertise.
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You’ll receive a certificates from our side
Frequently Asked Questions
What is the difference between the Live and Self-Paced courses?
-
Live Class:
- Offers real-time interaction with mentors.
- Includes scheduled live sessions where you can ask questions and get instant feedback.
- Provides personalized mentorship through live engagement.
-
Self-Paced Class:
- Access pre-recorded video content at your convenience.
- No fixed schedule – you can learn whenever it suits you.
- Get mentor support via pre-scheduled mentoring sessions without the need for live attendance.
Will I receive a certificate after completing the course?
Yes, upon successful completion of the course, you will receive a Certificate for Course Completion.
What type of projects will I be working on?
ou’ll be working on 5+ live projects that are designed to give you hands-on experience and practical knowledge.
How much mentor support is provided in the Self-Paced course?
The Self-Paced course offers 15+ hours of mentor training to help guide you through the course and projects.
How do I enroll in the Self-Paced course?
You can easily enroll in the Self-Paced course by clicking on the Enroll Now button and completing the registration process.
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