It will make you an expert in Machine Learning, a form of Artifificial Intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will master Machine Learning concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for your role with advanced Machine Learning knowledge
Key Features
- Experiential Learning
- Offline/Online Classes
- Case studies and assignments
- Hands on Projects
- Mentoring Sessions
- Job Assistance
Learning Pathway:
- Learn python program from scratch
- Statistical and mathematical essential for Data Science
- Data Science with python
- Machine Learning
- Natural language processing
- Database
- Django, Flask Application Development
- Data visualization techniques
Program Outcomes:
- Deep understanding of data structure and data manipulation.
- Understand and use linear non-linear regression models and classification techniques for data analysis.
- A comprehensive knowledge of supervised, unsupervised and Reinforcement learning models such as linear regression, logistic regression, clustering, decision tree, naive bayes, support vector machines, random forest, K-NN,K-means.
- Gain expertise in mathematical computing using the NumPy and Scikit-Learn package.
- Gain expertise in Exploratory data analysis using pandas, matplotlib and seaborn.
- Gain expertise in time series modeling.
- Understand deep reinforcement learning techniques applied in Natural Language Processing
- Understand the different components of the Hadoop ecosystem and learn to work with HBase, its architecture and data storage, learning the difference between HBase and RDBMS, and use Hive for partitioning.
- Understand MapReduce and its characteristics