AI & Machine Learning Premium Course for Free – Learn Everything Step by Step
[# AI & Machine Learning Premium Course for Free – Learn Everything Step by Step ] What You Will Learn in This Course 1. Introduction to AI & Machine Learning Understanding AI and its real-world applications Difference between AI, Machine Learning, and Deep Learning History and evolution of AI 2. Python for AI & Machine Learning Basics of Python programming Essential libraries: NumPy, Pandas, Matplotlib, Seaborn Data manipulation and visualization 3. Data Preprocessing & Feature Engineering Cleaning and handling missing data Data normalization and standardization Feature selection and dimensionality reduction 4. Supervised Learning Algorithms Linear Regression, Logistic Regression Decision Trees and Random Forests Support Vector Machines (SVM) Model evaluation and performance metrics 5. Unsupervised Learning Algorithms K-Means Clustering Principal Component Analysis (PCA) Anomaly detection 6. Deep Learning & Neural Networks Introduction to Neural Networks Building Deep Learning models with TensorFlow and Keras Convolutional Neural Networks (CNN) for image recognition Recurrent Neural Networks (RNN) for sequential data 7. Natural Language Processing (NLP) Text preprocessing techniques Sentiment analysis and text classification Transformers and Large Language Models (LLMs) 8. AI for Real-World Applications AI in Healthcare, Finance, and Marketing Deploying AI models in production Ethics and Bias in AI 9. Hands-on Projects & Certifications Real-world projects for portfolio building Best AI certifications for career growth Job opportunities and freelancing in AI This free premium course covers everything you need to become an AI and machine learning expert.
[# AI & Machine Learning Premium Course for Free – Learn Everything Step by Step ]
What You Will Learn in This Course
1. Introduction to AI & Machine Learning
- Understanding AI and its real-world applications
- Difference between AI, Machine Learning, and Deep Learning
- History and evolution of AI
2. Python for AI & Machine Learning
- Basics of Python programming
- Essential libraries: NumPy, Pandas, Matplotlib, Seaborn
- Data manipulation and visualization
3. Data Preprocessing & Feature Engineering
- Cleaning and handling missing data
- Data normalization and standardization
- Feature selection and dimensionality reduction
4. Supervised Learning Algorithms
- Linear Regression, Logistic Regression
- Decision Trees and Random Forests
- Support Vector Machines (SVM)
- Model evaluation and performance metrics
5. Unsupervised Learning Algorithms
- K-Means Clustering
- Principal Component Analysis (PCA)
- Anomaly detection
6. Deep Learning & Neural Networks
- Introduction to Neural Networks
- Building Deep Learning models with TensorFlow and Keras
- Convolutional Neural Networks (CNN) for image recognition
- Recurrent Neural Networks (RNN) for sequential data
7. Natural Language Processing (NLP)
- Text preprocessing techniques
- Sentiment analysis and text classification
- Transformers and Large Language Models (LLMs)
8. AI for Real-World Applications
- AI in Healthcare, Finance, and Marketing
- Deploying AI models in production
- Ethics and Bias in AI
9. Hands-on Projects & Certifications
- Real-world projects for portfolio building
- Best AI certifications for career growth
- Job opportunities and freelancing in AI
This free premium course covers everything you need to become an AI and machine learning expert.
