Machine Learning Using Python (AI/ML)

Artificial Intelligence (AI) and Machine Learning (ML) are breaking new ground in technology by transforming industries like healthcare, finance, and automation and driving innovations such as self-driving cars, virtual assistants, and predictive analytics. As the need for AI experts continues to rise, excelling skills in this field can lead to successful career paths. Sierra Learning offers one of the best Artificial Intelligence and Machine Learning (AI/ML) courses in Mangalore, with guaranteed placements and practical, real-world training to develop AI-powered applications, analyze data, and build predictive models. 

Course Modules:

1. Introduction to AI & ML

• Understanding Artificial Intelligence: Definitions, history, and impact on various industries.

• Machine Learning vs. Deep Learning: Differences, advantages, and real-world applications.

• Supervised, Unsupervised, and Reinforcement Learning: Core ML methodologies and when to use them.

• Ethical Considerations in AI: Bias in AI, fairness, and responsible AI development.

2. Python for AI & ML

• Introduction to Python and why it is the preferred language for AI and ML.

• Setting up the development environment (Anaconda, Jupyter Notebook, Google Colab).

• Python libraries for AI/ML: NumPy, Pandas, Scikit-Learn, TensorFlow, Keras, and PyTorch.

• Hands-on coding exercises for data manipulation, visualization, and basic model building.

3. Data Preprocessing & Feature Engineering

• Understanding the importance of clean data for ML models.

• Data collection, cleaning, and handling missing values.

• Feature selection and extraction to improve model accuracy.

• Normalization, standardization, and encoding categorical variables.

4. Machine Learning Algorithms

• Supervised Learning: Regression (Linear Regression, Polynomial Regression) and Classification (Logistic Regression, Decision Trees, Random Forest, Support Vector Machines, Naïve Bayes).

• Unsupervised Learning: Clustering (K-Means, Hierarchical Clustering, DBSCAN) and Dimensionality Reduction (PCA, t-SNE).

• Reinforcement Learning: Understanding Markov Decision Processes (MDP), Q-Learning, and applications in robotics and gaming.

5. Deep Learning & Neural Networks

• Introduction to Neural Networks: Perceptrons, Activation Functions, and Backpropagation.

• Building Deep Learning models using TensorFlow and Keras.

• Convolutional Neural Networks (CNNs) for image recognition and computer vision.

• Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTMs) for sequence modeling.

• Generative Adversarial Networks (GANs) for content creation and synthetic data generation.

6. Natural Language Processing (NLP)

• Text processing techniques: Tokenization, Lemmatization, and Stopword removal.

• Sentiment analysis, Named Entity Recognition (NER), and Text Classification.

• Word Embeddings: Word2Vec, GloVe, and BERT.

• Chatbot development and AI-powered language models.

7. AI in Computer Vision

• Image classification and object detection using OpenCV and TensorFlow.

• Face recognition, medical image analysis, and autonomous vehicle technology.

• Pose estimation and real-time video processing with AI.

8. AI Model Deployment & Optimization

• Model selection, tuning hyperparameters, and evaluating performance metrics.

• Deploying AI models using Flask, FastAPI, or TensorFlow Serving.

• Implementing AI solutions in cloud environments (AWS, Google Cloud, Azure).

• AI DevOps practices for maintaining and improving models in production.

9. Industry Applications of AI & ML

• AI in Healthcare: Disease diagnosis, drug discovery, and patient monitoring.

• AI in Finance: Fraud detection, credit scoring, and algorithmic trading.

• AI in Marketing: Personalized recommendations, ad targeting, and customer segmentation.

• AI in Cybersecurity: Threat detection, anomaly detection, and automated security responses.

• AI in Manufacturing: Predictive maintenance and quality control.

As Sierra Learning Academy provides one of the best AI/ML courses in Mangalore, the above AI/ML module has been carefully designed by our experienced trainers who are also industry professionals. Their deep knowledge and hands-on experience ensure the content is practical and relevant to current industry trends. The curriculum is designed to provide learners with real-world experience, equipping them with the essential skills to excel in AI and ML. With a focus on practical applications, it ensures guaranteed placements in promising and rewarding careers.

Benefits of This Course:

• Hands-on Learning: Work on real-world projects using Python, TensorFlow, and OpenCV.

• Expert-Led Training: Learn from experienced AI professionals and data scientists.

• Industry-Relevant Skills: Master AI tools and frameworks used in leading companies.

• Project-Based Curriculum: Build end-to-end AI solutions for different domains.

• Career Advancement: Enhance your resume and gain certifications for AI job roles.