Data Science For Beginners : Theory And Concepts
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English
| Duration: 3h 34m
Data science, AI, Machine Learning, Statistics
What you'll learn
Data science
Artificial intelligence
Machine Learning
Statistics and data analysis
Requirements
No prior experience in data science is required
Description
Are you eager to dive into the world of data science and unleash the power of data-driven insights ? My Data Science Fundamentals course is designed to equip you with essential skills and techniques required to excel in this rapidly growing field. Whether you're a beginner looking to start a career in data science or a professional seeking to enhance your analytical abilities, this course is tailored to meet your learning needs.Course Overview:In this comprehensive course, you will:Explore Data Science Foundations: Understand the fundamental concepts of data science, including data manipulation, exploratory data analysis (EDA), and data visualization techniques.Learn Statistical Analysis: Acquire foundational knowledge in statistics, hypothesis testing, and probability theory to make data-driven decisions and draw meaningful insights from data.Learn Machine Learning : Discover the principles of supervised and unsupervised learning, regression, classification, clustering, and evaluation metrics to develop predictive models.Learn Machine Learning Algorithms: Discover the principles of supervised and unsupervised learning, regression, classification, clustering, and evaluation metrics to develop predictive models.Introduction to Deep Learning: Dive into the basics of neural networks, deep learning, computer vision and natural language processing.Who Should Enroll:This course is ideal for:Aspiring Data Scientists and AnalystsBusiness and IT professionals seeking to leverage data for decision-makingStudents and researchers interested in exploring the field of data scienceNo prior experience in data science is requiredBy the end of this course, you will be equipped with the skills and confidence to tackle data science challenges, make informed decisions based on data analysis, and embark on a rewarding career in the dynamic field of data science.Join me on this exciting data science journey and unlock the potential of data-driven innovation !
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Foundations of Data science
Lecture 2 What is data science ?
Lecture 3 Role of a data scientist
Lecture 4 History and evolution of data science
Lecture 5 Data Preprocessing
Lecture 6 Overview of data storage
Lecture 7 Data Exploration and Visualization
Lecture 8 Descriptive Statistics
Lecture 9 Data Visualizations Techniques
Section 3: Statistical Foundations
Lecture 10 Importance of statistics
Lecture 11 Statistical Features Part 1
Lecture 12 Statistical Features Part 2
Lecture 13 Correlation
Lecture 14 Causation
Lecture 15 Probability Distribution
Lecture 16 Skewness
Lecture 17 Dimensionality Reduction
Lecture 18 Multicollinearity
Lecture 19 Outliers
Lecture 20 Bayesian Statistics
Lecture 21 Central Theorem Limit
Lecture 22 Sampling
Lecture 23 Confidence interval & Significance Level
Lecture 24 Features transformation
Lecture 25 Probability Theory
Lecture 26 Hypothesis Testing
Lecture 27 Regression Analysis
Lecture 28 Domain Knowledge
Section 4: Advanced Machine Learning
Lecture 29 Machine Learning concepts
Lecture 30 Machine Learning algorithms
Lecture 31 Supervised & Unsupervised Learning
Lecture 32 Cross Validation Techniques
Lecture 33 Metrics for Regression
Lecture 34 Metrics for Classification
Lecture 35 Deep Learning
Lecture 36 Introduction to Neural Network
Lecture 37 Artificial Intelligence & Robotics
Section 5: Congratulations
Lecture 38 Outro
Beginners curious about data science
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