AI/ML/DS/Data Analytics Batch 5 Track 2 Class – June 2023

Categories: Data Science
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About Course

Our Data Science Track 2 builds on the foundational concepts in our AI/DS/Analytics Track 1 and offers a more in-depth, deep dive into the domain of Advanced Analytics, Machine Learning and Artificial Intelligence. Our DS Track 2 presents an overview of machine learning concepts, algorithms, methodologies, and processes. Offering an introduction into the fundamental concept of deep learning with practical illustration of how deep learning is being applied in practice. This track will enable you to work on Data Science and Advanced Analytics projects with data from real-life, practical use-cases across different industries and sectors. You will be able to develop machine learning models using supervised and unsupervised learning algorithms such as regression, classification, clustering, and time series forecasting. You will also be exposed to two specialization in Artificial Intelligence: Computer vision for object detection, image / video analysis and text analytics using Natural language processing.

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Course Content

Class-01: Introduction to AI and ML Landscape
Introductory class to Ai and ML landscape

  • Class Video and Shared Resources
    00:00

Class-02: End-to-End Machine Learning Project
Understanding the steps involved in Machine Learning

Class-03 – Overview of ML Algorithms (Part 01)
Introduction to Machine Learning Algorithms

Class-04: Overview of ML Algorithms (Part 02)
An overview of ML Algorithms

Class-05: Overview of ML Algorithms (Part 03)
Understanding Machine Learning Algorithms

Class-06-Overview of ML Algorithms (Part 04) – Time Series Forecasting
Overview of Time Series Forecasting using ARIMA

Class-07: Natural Language Processing (Part 01)
Understanding NLP

Class-08-Natural Language Processing (Part 02)
Regular expression

Class-09-Natural Language Processing-Part-03 (SpaCy / DiffLib)
Focus on Introduction to SpaCy / Difflib

Class-10: Introduction to Computer Vision
Understanding Computer Vision

Class-11: Artificial Neural Network (Deep Learning)
Focus on Deep Learning

Class-12: Intelligent Automation
Understanding intelligent automation

Extra Resources for Class
Shared Extra Resources

Class Take Home Projects
Class Machine Learning projects for practice

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