The AI & Machine Learning Using Python course is designed to help learners acquire the skills needed to develop AI-powered solutions and build machine learning models. With a focus on practical applications, this course covers Python programming, key ML algorithms, and advanced AI concepts, making it ideal for aspiring data scientists, AI developers, and technology enthusiasts.

Course Highlights

• Duration: 80 hours (Weekday/Weekend options available)
• Mode: Online/Offline/Hybrid
• Prerequisites: Basic understanding of Python programming and mathematics (optional but recommended).

Key Learning Outcomes

• Gain a solid foundation in artificial intelligence and machine learning concepts.
• Master Python libraries for data manipulation, visualization, and machine learning.
• Build, train, and evaluate machine learning models for real-world applications.
• Explore deep learning techniques and frameworks like TensorFlow and Keras.
• Understand how to preprocess data, implement algorithms, and optimize models.

Modules Covered

1. Introduction to AI & Machine Learning

   • Overview of AI, ML, and Deep Learning
   • Real-world applications of AI and ML

2. Python for AI & ML

   • Python basics and advanced programming techniques
   • Libraries: NumPy, Pandas, Matplotlib, and Scikit-learn

3. Data Preprocessing and Analysis

   • Data cleaning, transformation, and visualization
   • Feature engineering and selection techniques

4. Machine Learning Algorithms

   • Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forests
   • Unsupervised Learning: K-Means, PCA, Clustering

5. Deep Learning Basics

   • Introduction to neural networks and backpropagation
   • Building deep learning models using TensorFlow and Keras

6. Natural Language Processing (NLP)

   • Text preprocessing, sentiment analysis, and language modeling
   • Implementing NLP tasks using libraries like NLTK and SpaCy

7. Computer Vision

   • Image processing and feature extraction
   • Building image classification models

8. Model Optimization and Deployment

   • Hyperparameter tuning and cross-validation
   • Deploying models with Flask or AWS

9. Real-World Projects and Case Studies

   • Predictive analytics, fraud detection, sentiment analysis, and more

Certification and Placement Assistance

• Certification Prep: Earn a course completion certificate recognized by industry professionals.
• Placement Assistance: Resume building, interview preparation, and access to our hiring network.

Who Should Attend?

• Students and graduates looking to start a career in AI and ML.
• Professionals aiming to upskill and transition to AI/ML roles.
• Enthusiasts passionate about exploring AI-driven technologies.

Why Choose Us?

• Learn from AI and ML industry experts.
• Hands-on projects to build real-world skills.
• Lifetime access to course materials and recorded sessions.