Overview of Machine Learning & Artificial Intelligence
Machine Learning & Artificial Intelligence jobs are high in demand and continue to be the winners in today’s world. This course is complemented with the Data science course offering students a wider platform of recognition of a Diploma in both fields. This area of study focuses on
- ✓ The importance of Machine Learning in the 21st century
- ✓ A brief outline of Artificial Neural Networks.
- ✓ Understanding the concept of Deep Learning
- ✓ A mathematical study and estimation of the learning models-Supervised and Unsupervised
Eligibility: Any graduate with programing aptitude and strong foundation in mathematics.
What you will learn
- Create a basic awareness of ML and AI using Python.
- Improve and develop methods and algorithms as applicable to ML and AI.
- Introduction to Artificial Neural Networks
- Algebraic & Geometrical Representation of Data
- Density Estimation based Supervised Learning Models
- Mathematical Perspective of Predictive Modelling
- Probability Perspective of ML
- Matrix Factorization of Unsupervised Learning Models
- Ensemble Models & Case Studies
- Introduction to Deep Learning
A computer is able to learn from experience without being explicitly programmed and hence the phenomenon of machine learning took its position in global markets. The popular data science methodologies come from machine learning. ML has a high rank in data science that the common view of a data scientist is someone that uses big data technologies to create pipelines that feed machine learning algorithms.
This curriculum covers the best-in-class modeling and data analytics techniques through a combination of lectures, self-learning, and project hours. To be an expert data scientist, practice, and experience count, our certificate course on “Data Science and Analytics” hence serve as a pre-requisite for this diploma course. This course focuses on ML technology with hands-on experience.
Benefits of Machine Learning & Artificial Intelligence
- Gain a better knowledge on Data Science project workflow and latest developments in field of machine learning.
- Understanding of Advanced Analytic tools and complex techniques in Statistics and ML.
- Big Data module covering topics like Spark, Hadoop and so on.
- Project completion results in a data product, a strong indicator of your expertise in the field of data science.
- Employability skills are enhanced with the current IT scenario with efficient project management skills.