hours of learning
- 36 hours
of live webinars
Artificial Intelligence & Machine Learning
Cloud & GPU Labs60+ Hours of Cloud & GPU Labs for Hands-on Practice, highest in the industry.
Online Lectures30+ Hours of Online Live Lectures by industry experts.
Hands-on ToolsGet hands-on experience with ML tools like Scikit Library, TensorFlow, Jupyter and Keras.
Free Python CourseFree course on Python Programming for Data Science worth Rs 8000 with the course.
Live Meet-UpsGet the chance to network with AI experts and enthusiasts through meetups.
Data Analytics and Data Science have become prominent parts of businesses today. Companies are leveraging analytics and data science to make intelligent business decisions and expertise in AI and ML is a way to do that. Also, certified AI and ML experts are considered an asset.
In this course, you will learn about various concepts in Machine Learning – its tools and algorithms. You will learn how to train and deploy ML models and go through a few AI concepts and AI applications like gaming and home automation. Programming in Python is also a skill you will pick up during the course. At the end of the course, you will get a certification from Manipal ProLearn, which is highly valued across industries.
Through experiential learning at Manipal ProLearn, you will develop expertise in several AI and ML concepts. Hands-on sessions with ML tools and the vast curriculum of the course ensure that you become proficient in training ML models and programming in Python. The course ensures that you upgrade your skills as a data scientist or a data analytics expert. You will
- Be able to perform data modelling and make predictions
- Gain knowledge on training and deploying ML models
- Use ML algorithms like Decision Trees and SVM and tools like Scikit Library, Keras and TensorFlow
- Use Jupiter Notebook as the development environment for Python
- Learn about the high-level concepts in Deep Learning, Text Analytics and NLP
- Focus on utilizing the data, tries to model it using various algorithms and helps in predicting.
- • Apply Scikit Learn library, and other machine learning and deep learning tools.
IT freshers wanting to start a career in the fields of AI and ML
Non-IT graduates with programming knowledge, keen on learning AI and ML
IT professionals and IT consultants who want to upgrade their knowledge
Business Intelligence professionals entering data analytics projects
Alpha Go and the rebirth of AI
Sneak peek into the future
Current trends in AI
Enterprise Applications of AI-Industries
Consumer Applications - Gaming, Home Automation
Understanding Artificial intelligence, Machine learning and Deep learning.
Use case driven comparison of AI, ML and DL
What is ML, Need for ML, classification of ML algorithms- supervised and unsupervised learning.
Types of ML algorithms
Classification and Regression – understanding classification and regression techniques with case studies
Introduction to Scikit- learn package in python.
Implementing ML algorithms in python using Scikit-learn
Linear, Logistic regression; Decision trees
Support Vector Machines. Python hand on using Scikit-learn
Creating training models using ML algorithms and deploying the models,
Understand how to deploy models after training
Basics of text processing, lexical processing, syntax and semantics of text processing,
other problems in text analytics
Introduction and applications of NLP.
Learning the business use cases of Natural language processing. Statistical NLP and text similarity,
syntax and parsing techniques, text summarization techniques, semantics and generation