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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study, Virtual Classroom	Video and Text Based

Course Overview

The Artificial Intelligence & Machine Learning Bootcamp by the Centre for Technology & Management Education (Caltech) via Simplilearn is an online Bootcamp. The course is designed to provide students with an understanding of the meaning, purpose, stages, applications, scope, and effects of Artificial Intelligence and Machine Learning. The Artificial Intelligence & Machine Learning Bootcamp certification syllabus covers key concepts of Machine Learning, Deep Learning, Statistics, Data Science with Python, Natural Language Processing, and Reinforcement Learning.

With Artificial Intelligence & Machine Learning Bootcamp online course, students will gain a deeper understanding of data science processes, data exploration, data visualization, data wrangling, hypothesis building, and testing. They will also acquire expertise in mathematical computing using the NumPy and scikit-learn package while mastering the concepts of supervised and unsupervised learning. Students and professionals from different industries and backgrounds who are eager to develop AI and ML expertise can join the Artificial Intelligence & Machine Learning Bootcamp certification course.

The Highlights

Caltech's Academic Excellence
IBM's Industry Expertise
Exclusive visit to Caltech’s Robotics Lab
Hands-on Experience
Certificate of completion

Programme Offerings

masterclasses
Caltech’s Robotics Lab
Online convocation by Caltech CTME Program Director
Access to hackathons
Seamless access to integrated labs
25+ hands-on projects
LevelUp Sessions
Simplilearn’s Career Assistance
Caltech CTME Circle Membership

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	IBMCaltech CTME

Eligibility Criteria

Candidates must have a bachelor’s degree in a relevant discipline.

Work Experience

Aspirants are required to have 5+ years of formal work experience.

Certification Qualifying Details

After successfully completing the Artificial Intelligence & Machine Learning Bootcamp certification course, students will receive a certificate from Caltech and an IBM certificate for IBM courses.

What you will learn

Machine learningKnowledge of Artificial IntelligenceKnowledge of Data Visualization

By pursuing the Artificial Intelligence & Machine Learning Bootcamp certification course, students will be able to:

Gain an in-depth understanding of Artificial Intelligence and Machine Learning.
Exposed to tools such as Keras to create computer vision applications.
Become familiar with generative adversarial networks (GANs).
Comprehend and appreciate Deep Learning and its applications.
Acquire know-how of Neural Networks, and traverse the layers of data abstraction to understand data like never before.

Who it is for

Machine Learning Engineer

The Artificial Intelligence & Machine Learning online course is designed for professionals from a variety of industries and backgrounds.
Students and professionals such as AI Engineers and ML Engineers who wish to advance their careers in the field of AI and ML can enrol in this course.

Admission Details

The admission process to the Artificial Intelligence & Machine Learning certification course includes the following steps:

Step 1: Filling and submission of Application Form

Step 2: Application Review

Step 3: Admission Confirmation

Application Details

Candidates can apply to this Bootcamp by following the below-mentioned instructions:

Visit the official website - https://www.simplilearn.com/ai-machine-learning-bootcamp#programDetails
Complete the application and submit
The application will be reviewed by a panel of admissions counselors
Qualified candidates will be offered admission to the course
Pay the course fee to block your seat

The Syllabus

Decoding Artificial Intelligence
Fundamentals of Machine Learning and Deep Learning
Machine Learning Workflow
Performance Metrics

Python Basics
Python Data Structures
Python Programming Fundamentals
Working with Data in Python
Working with NumPy Arrays

Data Science Overview
Data Analytics Overview
Statistical Analysis and Business Applications
Python Environment Setup and Essentials
Mathematical Computing with Python (NumPy)
Scientific Computing with Python (SciPy)
Data Manipulation with Pandas
Data Visualization in Python using Metplotlib

Introduction to Artificial Intelligence and Machine Learning
Data Preprocessing
Supervised Learning
Feature Engineering
Supervised Learning - Classification
Unsupervised Learning
Time Series Modelling
Ensemble Learning
Recommender Systems

AI and Deep Learning Introduction
Artificial Neural Network
Deep Neural Network and Tools
Deep Neural Net, Tuning, and Interpretability
Convolutional Neural Net (CNN)
Recurrent Neural Networks
Autoencoders

Computer Vision Basics with Python
Advanced Computer Vision with OpenCV 4, Keras, and TensorFlow 2
Computer Vision for OCR and Object Detection
PyTorch for Deep Learning and Computer Vision

Statistics Essentials For Data Science

Sample or Population Data?
The Fundamentals of Descriptive Statistics
Measures of Central Tendency, Asymmetry, and Variability
Practical Example: Descriptive Statistics
Distributions
Estimators and Estimates
Confidence Intervals: Advanced Topics
Practical Example: Inferential Statistics
Hypothesis Testing: Introduction
Hypothesis Testing: Let’s Start Testing!
Practical Example: Hypothesis Testing
The Fundamentals of Regression Analysis
Subtleties of Regression Analysis
Assumptions for Linear Regression Analysis
Dealing with Categorical Data
Practical Example: Regression Analysis

NLP and Speech Recognition

Introduction to Natural Language Processing
Feature Engineering on Text Data
Natural Language Understanding Techniques
Natural Language Generation
Natural Language Processing Libraries
Natural Language Processing with Machine Learning and
Deep Learning
Introduction of Speech Recognition
Signal Processing and Speech Recognition Models
Speech-to-Text
Text-to-Speech
Voice Assistant Devices

Reinforcement Learning

Introduction to Reinforcement Learning
Reinforcement Learning Framework and Elements
Multi-Armed Bandit
Markov Decision Process
Solution Methods
Q-value and Advantage-Based Algorithms

Caltech Artificial Intelligence and Machine Learning Bootcamp Masterclass

Instructors

Caltech CTME Frequently Asked Questions (FAQ's)

1: How will the Artificial Intelligence & Machine Learning Bootcamp classes be conducted?

The Artificial Intelligence & Machine Learning Bootcamp classes self-paced online videos and lives virtual classes.

2: What are the educational qualifications required for the Artificial Intelligence & Machine Learning certification course?

To pursue the Artificial Intelligence & Machine Learning certification by Caltech, students should hold a bachelor’s degree.

3: Do I require any work experience to apply for the Artificial Intelligence & Machine Learning online course?

It is preferable to have 5+ years of formal work experience to enrol in the Artificial Intelligence & Machine Learning training programme.

4: How can I apply for the Artificial Intelligence & Machine Learning online course?

To pursue the Artificial Intelligence & Machine Learning training programme, you need to fill up an online application form. You will be shortlisted based on your application by an admission panel. If shortlisted, you will be required to pay the programme fee to confirm your admission to the course.