Udemy - Ai, Machine Learning, Statistics & Python

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Free Download Udemy - Ai, Machine Learning, Statistics & Python
Published: 2/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.33 GB | Duration: 5h 16m
AI/ML : Overview, Statistics, Python, Machine learning, Methods, Use Cases in Telecom

What you'll learn
AI Basics
Machine Learning Overview
Types of Machine Learning
Deep Learning
Applications in Telecom
Introduction to Statistics
Overview of Python & its libraries
Descriptive Statistics
Central Tendency, Dispersion & Visualization (hands on - excel & python)
Probability and Distributions
Normal, Binomial & Poisson Distribution (hands on - excel & python)
Inferential Statistics
Hypothesis testing (t-tests)
Introduction to Supervised Learning
Linear Regression
Hypothesis, Cost function, Gradient Descent, Regularization
Logistic Regression
Sigmoid Function, Decision Boundary, Anomaly detection
Use cases in Telecom
Requirements
It is a course for everyone from beginner to expert level
Description
This course provides a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a focus on applications in the telecommunications industry. Learners will begin with an Overview of AI/ML concepts, followed by a deep dive into essential statistical foundations and Python programming for data analysis. The course covers key machine learning techniques, including supervised and unsupervised learning, model evaluation, and optimization methods. Finally, real-world use cases in telecom, such as network optimization, fraud detection, and customer experience enhancement, will be explored. By the end of the course, parti[beeep]nts will have a strong foundation in AI/ML and its practical implementations.Course includes -AI BasicsMachine Learning OverviewTypes of Machine LearningDeep LearningApplications in TelecomIntroduction to Statistics ·Overview of Python & its libraries ·Descriptive StatisticsCentral Tendency, Dispersion & Visualization (hands on - excel & python)Probability and DistributionsNormal, Binomial & Poisson Distribution (hands on - excel & python)Inferential StatisticsHypothesis testing (t-tests)Confidence IntervalIntroduction to Supervised LearningLinear RegressionHypothesis, Cost function, Gradient Descent, RegularizationExample of telecom networkLogistic RegressionSigmoid Function, Decision Boundary, Anomaly detectionExample of telecom networkThroughout the course, parti[beeep]nts will engage in hands-on projects and case studies, applying AI/ML techniques to real telecom datasets. By the end of the program, learners will have a strong technical foundation in AI/ML, practical coding skills, and the ability to implement AI-driven solutions tailored to the telecommunications sector.
Overview
Section 1: Introduction to AI & ML
Lecture 1 Introduction
Lecture 2 AI & ML Basics
Lecture 3 Machine Learning & its use cases
Lecture 4 Deep Learning & its use cases
Lecture 5 GenAI & its use cases
Lecture 6 Types of Machine learning
Lecture 7 Machine Learning in Telecom
Section 2: Statistics & Python: Foundation of AI/ML
Lecture 8 Introduction
Lecture 9 Statistics Basics
Lecture 10 Overview of Python
Lecture 11 Loop function in Python
Lecture 12 Conditional Statements & Visualization in Python
Lecture 13 Descriptive Statistics : Central Tendency
Lecture 14 Descriptive Statistics : Dispersion
Lecture 15 Descriptive Statistics : Visualization
Lecture 16 Data Distributions - Basics
Lecture 17 Probability Distribution
Lecture 18 Normal Distribution
Lecture 19 Z - Score
Lecture 20 Binomial Distribution
Lecture 21 Poisson Distribution
Lecture 22 Bayes' Theorem
Lecture 23 Inferential Statistics
Lecture 24 t - tests
Section 3: Supervised Learning
Lecture 25 Supervised Learning Overview
Lecture 26 Linear Regression
Lecture 27 Logistic Regression Overview
Lecture 28 Logistic Regression : Decision Boundary
Lecture 29 Logistic Regression : Cost Function
Lecture 30 Logistic Regression : Gradient Descent
Suitable for the engineers working in AI and IT/Telecom space or planning to get into technical domain of AI/ML and Telecom,Suitable for Managers working in telecom operators and planning to deploy or manage ML models in Telecom networks,Suitable for beginners who are interested to get into telecom domain and learn new technology such as AI/ML
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