At Tutorialspoint, our ultimate goal is to provide you with all the support you need for your professional career in AI/ ML. This Prime Pack is designed by the industry experts and academic leaders in such a way, that a beginner level developer or a non-coder will acquire the right set of knowledge and eventually become an expert in the field. For a programmer, who is already a machine learning expert, this course brings together almost all ML techniques and algorithms with case studies and Python programming. Each and every machine learning technique has been thoroughly explained with applications from real life.
In this Prime Pack, you will learn:
- Most used commonly to advanced supervised and unsupervised learning techniques.
- Beginner level Semi-supervised and Reinforcement learning.
- Python programming language for ML.
- Complete Probability and Statistics for ML.
- Deep Learning techniques.
- Application of deep learning in Computer Vision with OpenCV and Python.
- Machine Learning on Google Cloud Platform.
- Building ML model using BigQuery.
- Building ML model using GCP and TensorBoard.
All Spotle.ai courses, included in the Prime Pack, are compact and to the point. This helps you learn things quickly and give more time to applications building. Get ready for experiential learning.
Scope of Machine Learning and AI:
- As of 2022, Machine Learning Experts can earn as much as $118,000 a year!
- Machine learning is expanding in all fields such as banking, healthcare, IT, security, HR, etc.
- Some of the exciting applications of AI/ ML include Voice-based Personal Assistant, Self-driving Cars, Robotic Surgery, Fraud Detection, Disease Detection, etc.
Overview:
- 9 Modules
- 250+ Lectures
- 26 hrs of HD Videos
- Courses taught by Industry Experts and Academic Leaders
- Curriculum as per the most recent industry trends
- 360degree subject coverage
- Full life time access
- 30 days refund policy
- Certificate on each course completion
Projects:
- Hands-on Project - Building a machine learning model using BigQuery
- Hands-on project - Building a machine learning model using GCP and TensorBoard.
Goals
- The overview of Artificial Intelligence, Machine Learning, Deep Learning and Artificial Neural Networks.
- Hands-on - Different types of supervised learning techniques, such as Linear Regression, Logistic Regression, Decision Tree, Regression Tree, Discriminant Analysis, Naïve Bayes Classifier, K-NN, and their applications using Python.
- Hands-on - Different types of advanced supervised learning techniques, such as Support Vector Machines, Ridge Regression, Random Forest, and their applications using Python.
- Hands-on - Different types of advanced unsupervised learning techniques, such as K-means clustering, Hierarchical clustering, Principal Component Analysis, Factor Analysis, and their applications using Python.
- Hands-on - Different types of deep learning techniques and their applications using Python.
- How to choose the right set of algorithms to solve your problem statement.
- Application of Deep Learning in Computer Vision - Image Processing, Object Detection, Face Recognition, etc.
Prerequisites
- Passion to learn AI/ ML.
- A Computer with the Internet.
- Basic programming and statistics knowledge is a plus.
