Machine Learning and AI Fundamentals
Empower Your Future with Machine Learning and AI Fundamentals: Unlocking the Potential of Tomorrow’s Technology Today.
Early access to e-LMS included
About This Course
The Machine Learning and AI Fundamentals course offers a comprehensive introduction to the core principles of machine learning and artificial intelligence. Designed for AI professionals, this course covers supervised and unsupervised learning techniques, neural networks, deep learning, and natural language processing. Through a blend of engaging video lectures, interactive coding sessions, and real-world projects, participants will gain hands-on experience and practical skills, preparing them to excel in the AI industry.
Aim
To equip AI professionals with essential machine learning and AI skills, enabling them to innovate and excel in their careers.
Program Structure
Introduction to Machine Learning and AI
- Overview of Machine Learning and AI.
- Historical Context and Evolution.
- Key Terminologies and Concepts.
Supervised Learning
- Linear Regression and Classification.
- Decision Trees and Random Forests.
- Support Vector Machines (SVM).
- Model Evaluation and Performance Metrics.
Unsupervised Learning
- Clustering Algorithms (K-means, Hierarchical).
- Dimensionality Reduction Techniques (PCA, LDA).
- Anomaly Detection.
Neural Networks and Deep Learning
- Introduction to Neural Networks.
- Deep Learning Fundamentals.
- Convolutional Neural Networks (CNN).
- Recurrent Neural Networks (RNN).
- Transfer Learning.
Natural Language Processing (NLP)
- Text Preprocessing and Tokenization.
- Sentiment Analysis.
- Topic Modeling.
- Sequence Models and LSTM.
- Transformer Models and BERT.
Practical Machine Learning
- Working with Python and Jupyter Notebooks.
- Using TensorFlow and Keras for Model Building.
- Implementing PyTorch for Advanced Deep Learning.
- Utilizing scikit-learn for Machine Learning Algorithms.
Who Should Enrol?
- Senior undergraduates and graduate students in Computer Science and related fields.
- Professionals in IT, data science, and software development looking to enhance their AI skills.
Program Outcomes
- Gain a strong foundation in machine learning and AI principles.
- Develop proficiency in supervised and unsupervised learning techniques.
- Acquire hands-on experience with neural networks and deep learning models.
- Learn to implement natural language processing applications.
- Master the use of key machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, and scikit-learn.
- Complete real-world projects that demonstrate your ability to apply machine learning concepts.
- Earn a certificate of completion recognized by industry leaders, enhancing your professional credentials.
Fee Structure
Discounted: ₹10,999 | $164
We accept 20+ global currencies. View list →
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- 1:1 project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Publication Opportunity
Get published in a prestigious open-access journal.
Centre of Excellence
Become part of an elite research community.
Networking & Learning
Connect with global researchers and mentors.
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
View All Feedbacks →