Artificial Intelligence and Machine Learning with NLP

Duration: Hours

Training Mode: Online

Description

Introduction of Artificial Intelligence and Machine Learning with NLP:

Embark on a transformative journey into the realm of Artificial Intelligence (AI) and Machine Learning (ML) with a focus on Natural Language Processing (NLP) in this comprehensive training program at Locus Academy . Designed for aspiring data scientists, developers, and AI enthusiasts, this course offers a deep learning  into the fusion of AI and ML technologies, with a specific emphasis on NLP applications.

Participants will explore fundamental concepts and algorithms underpinning AI and ML, gaining hands-on experience in building and deploying NLP models for tasks such as sentiment analysis, text classification, language translation, and chatbot development through this training.

Through a blend of theoretical lectures, practical exercises, and real-world case studies, participants will master key techniques in data preprocessing, feature engineering, model training, and evaluation, equipping them with the skills needed to tackle complex NLP challenges across various domains.

Additionally, the course will cover emerging trends and best practices in AI and ML ethics, ensuring participants develop a responsible and ethical approach to deploying AI-powered NLP solutions. By the end of this training, participants will emerge as proficient AI and ML practitioners capable of harnessing the power of NLP to drive innovation and solve real-world problems effectively.

TABLE OF CONTENT

1: Introduction
1.1 Overview of Artificial Intelligence and Machine Learning
1.2 Introduction to Machine Learning
1.3 Historical Developments

2: Fundamentals of AI
2.1 Basics of AI
2.2 Problem Solving in AI
2.3 AI in Real-world Applications

3: Machine Learning Concepts
3.1 Machine Learning Overview
3.2 Types of Machine Learning
3.2.1 Supervised Learning
3.2.2 Unsupervised Learning
3.2.3 Reinforcement Learning

4: Data and Feature Engineering
4.1 Importance of Data in ML
4.2 Data Preprocessing
4.3 Feature Engineering

5: Model Development
5.1 Model Architecture
5.2 Training and Testing Models
5.3 Model Evaluation in AI and ML

6: Deep Learning
6.1 Introduction to Neural Networks
6.2 Deep Learning Applications
6.3 Convolutional Neural Networks (CNNs)
6.4 Recurrent Neural Networks (RNNs)

7: Natural Language Processing (NLP)
7.1 Basics of NLP
7.2 Text Processing and Analysis
7.3 NLP Applications

8: AI Ethics and Bias
8.1 Ethical Considerations in AI
8.2 Addressing Bias in Machine Learning
8.3 Responsible AI Practices

Please Visit AI and ML : || Locus Academy ha s more than a decade experience in delivering the training/staffing on Artificial Intelligence and Machine Learning with NLP for corporates across the globe. The participants for the training/staffing on Artificial Intelligence and Machine Learning with NLP are extremely satisfied and are able to implement the learnings in their on going projects.

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