Complete Python Bootcamp For Everyone From Zero to Hero 2025

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Complete Python Bootcamp For Everyone From Zero to Hero 2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 34.45 GB | Duration: 89h 34m​

Master Python Programming by building 100+ REAL PROJECTS . Learn OOP, Automation,GUI,REST and more to create your APPs.

What you'll learn
You will master the Python programming language by building 100+ projects.
Be able to use Python programming for data scraping and automation
Build GUIs and Desktop applications with Python programming
Create a portfolio of real Python projects to apply for developer jobs
You will learn Selenium, Beautiful Soup, Request, Flask, Pandas SQLite, MySQL, PostgreSQL, Seabon, and Matplotlib.

Requirements
No programming experience needed - you will learn everything you need to know.
Access to a computer with an internet connection.

Description
Welcome to Complete Python Bootcamp for Everyone, the best and the most comprehensive Python course on the internet. At 86+ hours, this Python course is without a doubt the most comprehensive and detailed Python course available anywhere online. If you are someone who has zero programming experience, this course will take you from beginner to professional.Learning Python is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! This course will help you in better understanding every detail of Python programming and how these concepts are implemented in high level programming language.We'll take you step-by-step through engaging video tutorials and teach you everything you need to succeed as a professional programmer.The course has been updated to be 2023 ready and you'll be learning the latest tools and technologies used at large companies such as Apple, Google, Microsoft, Amazon and more.This course explains everything in details with beautiful animated explanation videos and tens of real life projects which you will get to build. e.g. Ping Pong Game, Snake game, Blackjack , Form Filler and more.The curriculum was developed based on my 10+ years programming experience over a period of 2 years.We've taught over 100,000 students how to code and many have gone on to change their lives by becoming professional developers at top tech companies or starting their own tech startup.You do not need to waste your money on expensive bootcamps out there, the course teaches the same curriculum with lifetime access.The course is constantly updated with new content, with new projects and modules determined by students - it is a lifetime course.We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed as a Python developer.The course includes over 86+ hours of HD video tutorials and builds your programming knowledge while making real-world Python projects.The course will guide you master Python Programming language from beginner to advancedThroughout this comprehensive course, we cover a massive amount of tools and technologies, includingART 1 Getting Started With PythonSection 1 - Why We Program?Getting Started with PythonWhy Should You Learn to Write Programs?Computer Hardware ArchitectureInstalling Python on MacInstalling Python on WindowsLearning a New LanguageThe First Conversation with PythonWhat is a Bug? What are the Types of Bug?What is Debugging?Interpreter and CompilerBug, Debugging and Error TypesCode Editors and IDEsGetting Started with Code EditorsIntroduction QuizPrint StatementSolution to Print Statement Coding ExerciseSection 2 - Variables, Expressions and StatementsValues and TypesVariablesValues and Types QuizVariables QuizCoding Exercise Switch ValuesSwitch ValuesOperations and ExpressionsInput Function - Asking the User for InputCoding Exercise Input FunctionType Errors and Type ConversionComments in PythonVariable NamingVariable Naming QuizCoding Exercise - Data Types - Weeks in Yearsf Strings and Rounding NumbersMathematical Operations QuizSection 3 - Real Python Projects ( Variable, Expressions and Statements)Project 1 GreetingProject 2 Band Name GeneratorProject 3 Gross PayProject 4 Celsius to FahrenheitProject 5 Trip Cost CalculatorSection 4 - Conditional ExecutionBoolean ExpressionsConditional Execution (IF)Coding Exercise - Even or OddNested ConditionalsChained Conditionals (IF/ELIF/ELSE)Body Mass Index (BMI) CalculatorMultiple IF StatementsCoding Exercise - Burger OrderLogical OperatorsTry and ExceptConditional ExecutionSection 5 - Real Python Projects ( Conditional Execution)Project 6 - Gross Pay with OvertimeProject 7 - Leap YearProject 8 - Love CalculatorProject 9 - Gross Program using Try and ExceptProject 10 - Score CheckerSection 6 - Python FunctionsFunction Calls and Built in Functions - Type and Math FunctionsBuilt in FunctionsWhat is a Module? - Python Math ModuleModule QuizCoding Exercise - Area of CircleCoding Exercise - FactorialRandomisation in PythonCoding Exercise -Random - Coin TossCreating New Functions - User Defined FunctionsIndentation in PythonIndentation QuizFunctions in PracticeFunction with Inputs - Parameters and ArgumentsCoding Exercise - Area of SquareCoding Exercise - Volume ConverterPositional and Keyword ArgumentsCoding Exercise - Painting the WallFunctions with OutputsCoding Exercise - ConcatenateMultiple ReturnsPassword ControllerSolution to Password ControllerDocstringsPrint or Return?Why Functions?Section 7 - Real Python Projects (Python Functions)Project 11 - Leap Year with FunctionProject 12 - Gross Pay with FunctionsProject 13 - Cold, Warm and HotProject 14 - Maximum of Three NumbersSection 8 - Iteration (Lists)Understanding the ListsFor LoopUpdating VariablesCoding Exercise - Highest ScoreCoding Exercise - Find Integer NumbersCoding Exercise - Sum of Above Average ScoresLoop Over Custom FunctionUsing range() Function with For LoopCoding Exercise - Adding Odd NumbersCoding Exercise - Adding Even Numbers in ANY RangeFor Loop in PracticeWhile LoopWhile Loop in Practice - Hurdle 2Finishing iterations with CONTINUE and BREAKFactorial using LoopMaximum and Minimum of Input NumbersSection 9 - Real Python Projects (Iteration)Project 15 - Dice Rolling SimulatorProject 16 - Fizz Buzz GameProject 17 - Guessing the NumberProject 18 - Password GeneratorProject 19 - Rock, Paper and ScissorsPART 2 Python Data StructuresSection 10 - Introduction to Data StructuresWhat is a Data Structure?What is an Algorithm?Why are Data Structures and Algorithms important?Types of Data StructuresSection 11 - StringsWhat is a String?Coding Exercise - Sum of Digits of 2 Digit NumberString TraversalCoding Exercise - Backward TraversalCoding Exercise - Sum of DigitsCoding Exercise - Count Characters in a StringString OperationsCoding Exercise - First and Last 2 CharactersString MethodsCoding Exercise - Replace Character in a StringString Methods QuizParsing StringsEscape SequenceString FormattingCoding Exercise - Format a StringCoding Exercise - Print PatternProject 20 - String FormattingSection 12 - More on Python ListsMore on ListsCoding Exercise - Square Of ItemsIndex Out Of RangeList OperationsIndex QuizCoding Exercise - Reverse a List using Slice OperatorList Methods PracticeCoding Exercise - Update the First OccurrenceCoding Exercise -First and Last CharactersList and FunctionsCoding Exercise - Create a List from Two ListsCoding Exercise - Remove and AddCoding Exercise - Three Equal ChunksStrings and ListsCoding Exercise - Format ListNested ListCoding Exercise - Add Item in Nested ListCoding Exercise - Extend Nested ListObjects and ValuesCoding Exercise - List Addition with FunctionCoding Exercise - Concatenate Two Lists in One List Item WiseSection 13 - Real Python Projects (List)Project 21 - Bill RouletteProject 22 - Find the GoldProject 23 - Escaping the Maze (From Previous Section)Project 24 - Cryptography with Python Caesar CipherHow to Encrypt Data?Debugging Encrypt FunctionHow to Decrypt Data?Debugging Decrypt FunctionPutting Encrypt and Decrypt TogetherCode OptimizationProject 25 - Practice What We LearnedDividing the Program into StepsProject 26 - Putting Everything Together (Hangman)Section 14 - DictionariesWhat is a Dictionary?Creating Dictionary and Accessing Dictionary ElementsInsert/Update an Element in DictionaryCoding Exercise - Generate DictionaryTraverse / Search for Element in DictionaryCoding Exercise - Multiply Dictionary ItemsCoding Exercise - Student GradesRemove Elements from DictionaryCoding Exercise - Rename KeyIN / NOT IN Operators with DictionaryCoding Exercise - Count Characters in a WordNested DictionariesHandling Missing Keys in Dictionary - get() and setdefault() methodsKeys in Dictionary - fromkeys() and keys() methodsCoding Exercise - Group Value TypesDictionary items() MethodCoding Exercise - Length of Dictionary ValuesDictionary update() MethodCoding Exercise - Concatenate Three DictionariesDictionary values() MethodCoding Exercise - Remove Empty ItemsReference to Dictionary - copy() MethodCoding Exercise - Merge Two DictionaryDeep CopyCoding Exercise - Custom Deep Copy for List ValuesDictionary Operations and built in Python FunctionsDictionary vs ListDictionary QuizSection 15 - Real Projects (Dictionary)Project 27 - Calculate Total PriceProject 28 - Blind Auction ProgramProject 29 - Quiz APPSection 16 - TuplesWhat is a Tuple?Why Tuples?Unpacking TuplesCoding Exercise Sum Tuple Elements using UnpackTraverse Tuple - Enumerate()Coding Exercise Even Index with EnumerateSearching in TupleTuple Operations / FunctionsCoding Exercise Find Most Frequent ItemNested TuplesNested Tuple IndexingTuple vs ListCoding Exercise Convert Tuple to DictionaryTuple QuizProject 30 - English to Pig LatinProject 31 - Music APPSection 17 - SetsWhat is Set? Set TerminologySets in PythonSet MembershipAdding Members to SetCoding Exercise Adding Members from ListCoding Exercise Remove DuplicatesDeleting Items from SetDelete Restricted Items Using Remove MethodUnion SetCoding Exercise Combine SetsCoding Exercise Union List of SetsSet IntersectionSet SubtractionSet Symmetric DifferenceModifying SetsSubsets and SupersetsSection 18 - Real Projects (Sets)Project 32 - Powerball LotterySection 19 - Data Structures and Algorithms in PythonPython Programming Data StructuresPython Programming AlgorithmsPART 3 Recursion, Regular Expressions, Files and OOPSection 20 - RecursionWhat is Recursion?Why do we need Recursion?The Logic Behind RecursionRecursive vs Iterative SolutionHow to write a recursive solution in steps?Fibonacci Numbers using RecursionCoding Exercise 'a' to the power 'b' - using RecursionSection 21 - Project 33 - Flooder Gamebext Module in PythonSection 22 - Scope in PythonGlobal vs Local ScopeBlock Scope in PythonModify Global VariablePython Constants and Global ScopeScope QuizProject 34 - BlackJack - Practice What we have learntSection 23 - Debugging - Find and Fix Programming ErrorsIdentify the Problem (Error)Reproduce the BugAnalyse Each LineFix Errors - IDE MessagesUsing print() in DebuggingDebugger ToolsError Types - Syntax ErrorsRuntime ErrorsLogical ErrorsHandling the ErrorsRaise Your Own ExceptionsHandling ExceptionsSection 24 - Regular expressionsWhat is Regular Expression?MetacharactersGroups and AlterationRepetition in Regular Expression Patterns ( ?, *,)Greedy and Non Greedy MatchesCharacter ClassesCustom Character ClassesCaret, Dollar and Dot / Dot-StarAnchorsGrouping ConstructsRegex Matching with Flagsre Searching Functionsre Substitution Functionsre Utility FunctionsProject 35 - Phone and Email ScraperSection 25 - Local Development Environment - Installing PyCharmSteps for setting up Local Development EnvironmentDownload PyCharm (Windows/Mac)Install PyCharm on MacInstall PyCharm on WindowsCommon Features of PyCharmProject 36 - Strong Password Detection using Local Development EnvironmentSection 26 - Files and DirectoriesFile SystemsTerminal on Mac and Command Prompt WindowsRelative and Absolute File PathsQuiz PathsNavigate the File System with OS ModuleGet File Details with OS ModuleList All Files in Directory RecursivelyFilename Matching with glob ModulePython's New Pathlib ModuleOperating System DifferencesFind Last Modified File using PathlibFile System Modules (os, glob, pathlib)Project 38 - Display a Directory TreeProject 39 - Rename all Files in a Directory TODOOpen and Read Files Text FilesFile Cursor, Read Line and Read LinesSearching Through a FileReading File Challenge / ExerciseParsing Text FileFile ModesWriting to FilesPrinting a Text to FilesTime Table Exercise - (File Writing)What is a Binary File?Writing and Reading to Binary FileShelve ModuleData Manipulation with ShelveMoving and Copying FilesDeleting FilesProject 40 - Quiz using FilesSection 27 - Object Oriented Programming - OOPWhat is OOP? Why we need it?Object Oriented ThinkingOOP Concepts Classes, Objects, Attributes and MehtodsConstructing Objects - Accessing Attributes and MethodsBlackJack OOPClasses - Create Your Own ClassClass AttributesClass MethodsChecking Instance TypesEncapsulationGetters and SettersInheritanceInheritance with ParametersInheritance ChallengeOverriding MethodsProject 41 - Bike Rental System using OOPdatetime Module in PythonPART 4 PYTHON AUTOMATION - Automate Daily ROUTINE TASKSSection 28 - Excel Automation - Openpyxl LibraryIntroduction - Advantages and Use Cases of OpenpyxlReading Excel SpreadsheetsIterating Through ExcelColumns, Rows and CellsManipulate Excel DataProject 42 - Automate Daily Routine Excel TaskCreate Spreadsheet, Sheets and Update CellsManage Rows and ColumnsGenerate Random Excel Data - ChallengeExcel FormulasCell StylesConditional FormattingChartsLine Charts - Coding ChallengeProject 43 - Transpose Excel File from Rows to ColumnsSection 29 - PDF AutomationExtract PDF Metadata and TextCreate, Merge and Copy PDFsSplit, Rotate and OverlayDecrypt and EncryptProject 44 - Combine Specific Pages (add cover page) to PDFSection 30 - Web Scraping with Beautiful SoupWhat is Web Scraping?Basic HTML SkillsParsing HTML with Beautiful SoupFind and Select Specific ElementsSteps for Web Scraping a Real WebsiteDo All Websites Allow Web Scraping?Project 45 - Beautiful Soap - Airpods rating on AmazonSection 31 - Selenium Library - Python BOTsWhy Selenium?Setup SeleniumHow Select Elements in WebsiteScrap Data using SeleniumHow to Clicking Buttons and Filling Text FieldsSending Special Keys and Browser ButtonsProject 46 - Selenium - Follow on InstagramSection 32 - GUI AutomationWhat is GUI Automation? Installing PYAUTOGUI ModuleMouse MovementMouse InteractionMouse Drag - ChallengeScreenshot and Image RecognitionControlling the Keyboard and Show MessagesProject 47 - GUI Automation - Looking BusyProject 48 - Form FillerSection 33 - Working with CSV Data - The PandasReading CSVData Types and Basic StatisticsPandas Data Structures - SeriesAccessing Series ElementsPandas Data Structures - DataFrameAccessing DataFrameQuery DatasetGroup and Aggregate the DataWrite to CSVPART 5 - Graphical User Interface (GUI) in PythonSection 34 - Turtle ModuleIntroduction to Turtle GraphicsMove TurtleDraw Shape - ChallengeDrawing and Filling Present ShapesDrawing PolygonsDraw Dashed ShapesRGB Color - Generate Random ColorScreen and Turtle PropertiesMove Random Directions - ChallengeHow to Create Games with TurtleWrite Method - Default Values for Function ArgumentsProject 49 - Draw PandaProject 50 - Draw National Flag of IndiaProject 51 - Draw National Flag of Your COUNTRYProject 52 - Schengen CountriesProject 53 - Turtle RaceProject 54 - Snake Game using OOPSection 35 - Tkinter ModuleIntroduction to TkinterCreating and Configuring WidgetsUnlimited Positional and Keyword Arguments (*args and **kwargs)Widget Placement - Geometry ManagersHandling EventsLabel WidgetButton WidgetCheck and Radio ButtonsEntry WidgetCombobox and SpinboxProgress Bar and ScaleOrganize Widgets with FrameFrame WidgetTop Level Window WidgetPaned Window WidgetNotebook Widget - TabsProject 55 - Feedback FormProject 56 - Pomodoro AppProject 57 - Text EditorPART 6 - Working with Databases in Python Section 37 - Introduction to DatabasesSection 38 - Using SQLite in PythonSection 39 - Project 58 - Password Manager using SQLiteSection 40 - SQLAlchemy CoreSection 41 - Project 59 - Password Manager using SQLAlchemy CoreSection 42 - SQLAlchemy ORMSection 43 - Project 60 - Password Manager using SQLAlchemy ORMSection 44 - Using MySQL in PythonSection 45 - Project 61 Employee Management System using MySQLSection 46 - Using PostgreSQL in PythonSection 47 - Project 62 - HCM using PostgreSQLPART 7 - Advanced PythonSection 48 - List ComprehensionSection 49 - Project 63 - NATO Phonetic AlphabetSection 50 - Lambda FunctionsSection 51 - GeneratorsSection 52 - DecoratorsSection 53 - Project 64 - Cache Fibonacci SeriesSection 54 - Applications Programming Interfaces (APIs)Section 55 - Project 65 - Random Joke Generator APISection 56 - Project 66 - International Space Station Location APISection 57 - Web Services - RESTful APIs with FlaskSection 58 - Data Analyses and VisualizationMatplotlibSeabornSection 59 - Real ProjectsProject 66 - 100Sign up today, and look forward to:Video LecturesLecture SlidesCode Challenges and ExercisesReal Life ProjectsQuizzesProgramming Resources and NotesDownloadsDon not just take my word for it, check out what existing students have to say about my courses:"Great explaining and has a ton of exercises, and he is updating it till this day. He codes a lot in the course, and he is fast at it, so for people looking for a fast paced course, this is a great option!." - Hyper O."The teacher is great! he explains everything in full details especially with real life examples. he uses the right algorithm in making his teaching methods effective so students don't get bored and sleepy." - Precious Ogbonna Nwakama"Nicely explained with graphics for non non programmers. Thank you. Amazingly simple to understand. Best wishes to the instructor." - Shahnawaz Ayon"- Amazing Explanation-The guy explains everything.-He explains with diagrams. Then with algorithm. Then with code.-This three times explanation makes the topics very retentive for a learner.." - Abinash Dash"Thats how a course should be! Excellent explanation and lot of coding excercises to practice.I read some comments on the accent of the trainer being not so good and all, but its very clear in fact!Am excited for the next sections.." - Siddhesh Sule"Excellent course for those looking to understand data structures and algorithms from beginner to advanced level. The theoretical explanations are well done, along with concrete real life examples. All data structures and algorithms described and then implemented, which makes the concepts easier to understand and gives you a chance to apply them in a real practice. The top tech's interview questions and answers sections are excellent bonus which allow for preparing real interviews."- Johanna DavidSo what are you waiting for? Click the buy now button and join the world's best and most comprehensive development course.

Who this course is for:
If you want to learn Python from scratch through building fun and useful projects, then take this course., If you want to start your own startup by building your own apps., If you are an experienced programmer wanting to switch to Python then this is the quickest way through real coding projects., If you are an intermediate Python programmer this course will help you to level up.

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Python Bootcamp
Published 9/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.63 GB | Duration: 9h 36m​

Master Python and unlock power of data with NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, and PyTorch

What you'll learn

Gain a thorough understanding of Python syntax, script writing, and core concepts such as variables, data types, and string operations

Master the use of conditional statements and loops in Python to automate and optimize data processing tasks

Learn to design reusable Python functions to perform repetitive tasks efficiently, including recursion and lambda functions

Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance

Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format

Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python

Gain hands-on experience with Scikit-Learn, applying supervised and unsupervised learning algorithms to solve real-world machine learning problems

Understand the fundamentals of Deep Learning and neural networks, forming the foundation to work with TensorFlow and PyTorch frameworks

Build and evaluate deep learning models in PyTorch, including projects such as Fashion MNIST classification and cancer prediction

Requirements

No prior experience in Python or data analysis is required; just basic computer skills and access to a computer with an internet connection are necessary to start this course.

Description

Are you looking to build a career in data science or elevate your data analysis skills? Do you often wonder how professionals transform raw data into meaningful insights that drive decisions? If your goal is to confidently step into the world of Python programming, machine learning, and deep learning, then this course is your complete guide.Python Bootcamp is a comprehensive bootcamp designed to take you from the fundamentals of Python all the way to advanced data science applications. Whether you are a beginner or someone with prior programming experience, this course will equip you with the knowledge and practical skills required to thrive in the data-driven world.By enrolling in this course, you will:Build a strong foundation in Python programming - from basic syntax, data types, and loops to advanced functions and file handling.Master essential data science libraries including NumPy for numerical computing, Pandas for data manipulation, and Matplotlib and Seaborn for powerful data visualizations.Gain expertise in machine learning with Scikit-Learn, exploring supervised and unsupervised learning techniques, model selection, and evaluation.Dive into deep learning fundamentals, learning how neural networks work and how to implement them using TensorFlow and PyTorch.Work on real-world projects, including classification tasks with datasets like Fashion MNIST and Melanoma Cancer Prediction, applying everything you learn in practical scenarios.Develop end-to-end data analysis workflows - from data cleaning and transformation to visualization and predictive modeling.Why this course is essential for you:In today's data-driven landscape, the ability to analyze, visualize, and model data is one of the most in-demand skills across industries. Python stands out as the most popular and versatile language in data science, powering everything from academic research to business intelligence and AI innovation.This bootcamp doesn't just teach you concepts; it empowers you to apply them immediately. Through hands-on coding exercises, projects, and guided assignments, you will not only understand the "how" but also the "why" behind each step.What makes this course unique?A step-by-step journey from beginner-friendly Python programming to advanced machine learning and deep learning.A practical, project-driven approach - learn by doing, not just by theory.Coverage of the entire data science ecosystem - from NumPy, Pandas, and visualization tools to Scikit-Learn, TensorFlow, and PyTorch.Real-world datasets and case studies to prepare you for professional data challenges.Don't let data feel overwhelming anymore. Take charge and transform it into actionable insights.Enroll in Python Bootcamp today and begin your journey toward becoming a confident, skilled, and job-ready data professional.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Course resources

Section 2: Getting Started with Python

Lecture 3 What is Python & Why Learn It?

Lecture 4 This is a Milestone!

Lecture 5 Understanding Variables in Python

Lecture 6 Python Data Types

Lecture 7 Working with Strings in Python

Lecture 8 Useful String Methods

Section 3: Data Structures in Python

Lecture 9 Lists in Python

Lecture 10 Understanding Tuples

Lecture 11 Working with Dictionaries

Lecture 12 Sets in Python

Section 4: Conditional Statements in Python

Lecture 13 Introduction to Conditional Statements

Lecture 14 Operators and Advanced Conditions

Section 5: Loops in Python

Lecture 15 For Loops in Python

Lecture 16 While Loops in Python

Section 6: Functions in Python

Lecture 17 Defining and Using Functions

Lecture 18 Understanding Recursion

Lecture 19 Lambda Functions in Python

Section 7: File Handling in Python

Lecture 20 Reading and Writing Files in Python

Section 8: Machine Learning Basic

Lecture 21 Introduction to Machine Learning

Section 9: Numpy Library

Lecture 22 Overview of NumPy and Its Core Concepts

Lecture 23 Indexing and Selecting Data in NumPy Arrays

Lecture 24 Understanding Array Data Types, Shapes, and Stacking

Lecture 25 Techniques for Creating Arrays in NumPy

Lecture 26 Performing Mathematical and Statistical Operations with Arrays

Section 10: Pandas Library

Lecture 27 Introduction to Pandas DataFrames

Lecture 28 Working with Series and DataFrames

Lecture 29 Core Methods for Data Analysis in Pandas

Lecture 30 Handling Missing and Null Data

Lecture 31 DataFrame Transformation and Manipulation

Section 11: Matplotlib Library

Lecture 32 Getting Started with Matplotlib Library

Lecture 33 Plotting Fundamentals: Creating and Customizing Visuals

Lecture 34 Subplots and Scatter Plots: Comparative and Relational Analysis

Lecture 35 Bar Charts, Histograms, and Pie Charts: Distribution and Composition Insights

Section 12: Seaborn Library

Lecture 36 Introduction to the Seaborn Library

Lecture 37 Visualizing Distributions: Univariate and Bivariate Analysis

Lecture 38 Advanced Plots in Seaborn: Pairplots and Barplot Customization

Lecture 39 Complex Visualizations: Countplots and Heatmaps

Section 13: Scikit-Learn (sklearn) Library

Lecture 40 Introduction to Scikit-Learn and Environment Setup

Lecture 41 Data Loading Utilities in Scikit-Learn

Lecture 42 Supervised Learning with Scikit-Learn

Lecture 43 Unsupervised Learning with Scikit-Learn

Lecture 44 Data Transformation Techniques in Scikit-Learn

Lecture 45 Model Selection and Evaluation in Scikit-Learn

Lecture 46 Visualization Tools in Scikit-Learn

Lecture 47 Saving and Reusing Models in Scikit-Learn

Section 14: Deep Learning Basic

Lecture 48 Introduction to Deep Learning

Section 15: Tensorflow Framework

Lecture 49 Introduction to TensorFlow

Lecture 50 Working with Tensors and TensorFlow Operations

Lecture 51 Key Components of TensorFlow

Lecture 52 Building Models with Keras in TensorFlow

Lecture 53 Understanding the Variety of Layers in Neural Networks

Lecture 54 Project - Fashion MNIST Classification with TensorFlow

Section 16: PyTorch Framework

Lecture 55 Introduction to PyTorch

Lecture 56 Tensor Operations in PyTorch

Lecture 57 Building Neural Networks with PyTorch

Lecture 58 Project - Melanoma Cancer Prediction with PyTorch

Lecture 59 Project Extension - Data Augmentation for Cancer Prediction

Lecture 60 Project Extension - Defining a Custom Neural Network

Lecture 61 Evaluating Models with Confusion Matrix in PyTorch

Lecture 62 The final milestone!

Section 17: Conclusion

Lecture 63 About your certificate

Lecture 64 Bonus Lecture

Complete beginners who want to learn Python programming step by step, starting from the basics and moving towards advanced applications.,Aspiring data scientists and analysts who want a structured, hands-on pathway to mastering Python libraries like NumPy, Pandas, Matplotlib, Seaborn, and Scikit-Learn.,Software developers, engineers, and IT professionals looking to expand their skill set into data analysis, machine learning, and deep learning.,Students and academic researchers who want to apply Python programming to analyze datasets, visualize results, and gain actionable insights for projects and publications.,Professionals working with business data, marketing analytics, or finance who want to automate data processing and generate meaningful insights efficiently.,Enthusiasts interested in deep learning, and neural networks who want practical exposure to frameworks like TensorFlow and PyTorch through real-world projects.

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