Diploma Artificial Intelligence

Diploma Artificial Intelligence

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 6Month/60 Hours                                                  Price:120,000

                                                                                      110,000

Diploma Artificial Intelligence


In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project.

This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.


Course Key learnings:
The course provides the entire toolbox you need to become a data Analyst.
Impress interviewers by showing an understanding of the data science field
Learn how to pre-process data
Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
Start coding in Python and learn how to use it for statistical analysis
Perform linear and logistic regressions in Python
Carry out cluster and factor analysis
Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
Apply your skills to real-life business cases
Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
Unfold the power of deep neural networks
Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations.
Build an AI
Understand the theory behind Artificial Intelligence
Solve Real World Problems with AI
Master the State of the Art AI models
Q-Learning
Deep Q-Learning
Deep Convolutional Q-Learning
A3C

Course Outline

Module1:Introduction

 The Various Data Science Disciplines
Connecting Data Science Discipline
Benefits of Discipline
Popular Data Science Techniques
Poular Data Science Tools
Carrers in Data Science
Debunking Common misconception

Module2: Probability

Probability Combinations
Bayesians Inference
Distributions
Probability in Other Fields

Module3: Statics

Descriptive Statics
Inferential Statics Fundamentals
Inferential Statics:Confidentals Intervals
Practical Examples

Module4: Python

Introduction To Python
Variables & Data Types
Basic Python Syntax
Python Operators
Conditional Statement
Python Functions
Sequence
Iterations
Advanced Python Tools
Advanced Staticals method in Python

Method5:Advanced Statistical Methods in Python

Advanced Statistical Methods-Liner Regression with Stats Model
Advanced Statistical Methods-Multiple Liner Regression with Stats Model
Advanced Statistical Methods-Liner Regression with sklearn
Advanced Statistical Methods-Practical Example
Advanced Statistical Methods-Logistic Regression
Advanced Statistical Methods-Cluster Analysis
Advanced Statistical Methods-Other Types of Clustering

Module6: Mathematics

What is a Matrix
Scalars and Vector
Scalars and Vector
Linear Algebra and Geometr
Linear Algebra and Geometr
Arrays in Python – A Convenient Way To Represent Matrice
What is a Tensor
What is a Tensor
Addition and Subtraction of Matrice
Addition and Subtraction of Matrice
Errors when Adding Matrice
Transpose of a Matri
Dot Produc
Dot Product of Matrice
Why is Linear Algebra Useful?

Module7: Deep Learning

Introduction to Neural Networks
How to Build a Neural Network from Scratch
TensorFlow
Introducing Deep Neural Networks
Overfitting
Intializing
Preprocessing
Classifying on the MINIST Database

Module8:Fundamentals of Reinforcement Learning

Fundamentals of Reinforcement Learning
Q Learning Intitution
Q-Learning Visualization

Module9:Deep Q-Learnings

Deep Q-Learning Intution
Deep Q- Learning Implementation
Deep Q-Learning Visualization

Module10: Deep Convolutional Q-Learning

Deep Convolutional Q-Learning-Intution
Deep Convolutional Q-Learning-Implementation
Deep Convolutional Q-Learning-Visualization

Module11 :A3C

A3C-Intution
A3C-Implementation
A3C-Visualization

Requirements
High School Maths
Basic Python knowledge
Who this course is for:
Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning

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