infyni

Live Artificial Intelligence and Machine Learning Course

Join our live online course to delve into Artificial Intelligence and Machine Learning. Learn essential concepts, algorithms, and practical applications through hands-on projects.

Live Course

Live Class: Tuesday, 12 Dec

Duration: 45 Hours

Enrolled: 0

Offered by: infyni

Live Course

About Course

Embark on a journey into the realms of Artificial Intelligence (AI) and Machine Learning (ML) with our live online course. Explore foundational concepts, algorithms, and applications of AI and ML. Dive into supervised and unsupervised learning techniques, neural networks, deep learning, and more. Engage in hands-on projects and real-world case studies to develop a robust skill set and become proficient in leveraging AI and ML technologies.

Skills You Will Gain

Fundamentals of AI and ML Supervised Learning Algorithms Unsupervised Learning Techniques Neural Networks and Deep Learning Natural Language Processing (NLP) Deployment and Scaling ML Models Ethical AI and Bias Mitigation

Course Offerings

Instructor-led interactive classes
Clarify your doubts during class
Access recordings of the class
Attend on mobile or tablet
Live projects to practice
Case studies to learn from
Lifetime mentorship support
Industry specific curriculum
Certificate of completion
Employability opportunity

Topics
Instructor (1)

1 Introduction

2 Optimization and its application in Machine learning

3 Statistical Inference

4 An introduction to linear algebra for Machine Learning

5 Exploratory Data Analysis and the Data Science Process

6 Basics of Machine Learning and Introduction to statistical learning

7 Introduction to simple Linear & Multiple Linear Regression

8 Case Study on Regression using kaggle data set

9 Regularization as a general concept and its use in Linear Regression

10 General intuition behind feature engineering and its relevance in Machine learning

11 Introduction to Classification Algorithms

12 Case study on classification Using real life data set( Kaggle / Analytics Vidya)

13 Feature selection methods and their relevance

14 Clustering

15 Neural Networks and Deep Learning (FFN, CNN, RNNs)

16 Model Agnostics

Saurabh lal

About Instructor

I come from a mathematical background and love mentoring students. Teaching is more than a profession for me, So every engagement with my students is special.

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