Python Full Course for Beginners to Advanced with AI (2026)

Learn Python from Beginner to Advanced with AI in this complete course! Master Python step-by-step with real-world projects and no prior experience. 📥 Download the Full Python Course Notes (Free): https://www.theiscale.com/DataAnalyti... In this video, you will learn: ✅ Python basics (variables, loops, functions) ✅ Advanced concepts (OOP, modules, projects) ✅ How to use AI tools with Python ✅ Real-world projects step-by-step 💡 This course is perfect for: Beginners with no coding experience Students & developers Anyone who wants to learn Python with AI ⏱️ Timestamps: 00:00:00 – Intro: Python in AI ecosystem. 00:01:24 – Roadmap: Salary metrics & Tech roles (DA, DS, AI). 00:02:13 – Resources: Manual, Codebase & Datasets. 00:05:08 – Python vs LLMs: Scripting power vs AI limitations. 00:06:22 – Demo 1: Local File System (OS) operations. 00:08:18 – Demo 2: Hardware access (Peripherals control). 00:09:50 – Demo 3: Automated Web Scraping script. 00:14:51 – Anaconda: GUI environment setup. 00:16:26 – Installation: Step-by-step 64-bit config. 00:19:12 – Jupyter: Launching kernel 00:21:01 – Jupyter Mastery: Markdown vs Code cells. 00:21:52 – Unit 1: "Hello World" implementation. 00:22:51 – System Check: Runtime versioning via sys. 00:23:52 – Comments: Single-line (#) & Multi-line strings ("""). 00:26:46 – Unit 2: Variables & E-commerce data modeling. 00:28:47 – Naming Rules: 00:31:09 – Sensitivity: Case-sensitive variable auditing. 00:33:41 – Primitives: int vs float precision. 00:34:39 – Advanced Primitives: str & complex numbers. 00:35:39 – Collections: Initializing list, tuple, dict & set. 00:38:14 – Arithmetic Ops: Binary operators (+, -, *). 00:40:42 – Division/Modulus: / quotient vs % remainder. 00:41:58 – Exponentiation: Power calculation using **. 00:46:23 – Unit 3: Built-in function reusability logic. 00:47:38 – eval(): 00:50:12 – abs(): 00:53:01 – sum(): 00:55:00 – pow(): 00:56:00 – input(): 00:58:37 – Type Casting: int(), float() & str() conversion. 01:03:35 – len(): 01:07:30 – Unit 4: Conditional logic & Boolean flow. 01:10:30 – if Logic: 01:14:29 – if-else: 01:18:28 – if-elif-else: 01:27:03 – AI Study: Automating summaries via NotebookLM. 01:31:25 – Unit 5: Iterative logic & repetition psychology. 01:34:35 – while Loops 01:38:53 – Safety: Infinite loop recovery 01:41:12 – for Loops 01:42:56 – range(): start, stop, step parameters. 01:44:24 – Iteration: 01:45:32 – break 01:48:27 – continue: Skipping current iteration. 01:52:40 – Unit 6: User-Defined Functions 01:56:05 – def keyword 01:57:33 – Mini-Project 02:04:11 – Parameters: Handling dynamic Arguments. 02:10:46 – Recruiter Quiz: AI-driven technical assessment. 02:13:25 – Strings: Positive/Negative indexing & Slicing. 02:27:16 – String Methods: .upper(), .lower(), .replace(), .find(). 02:34:17 – Lists: Mutability, indexing & item assignment. 02:46:48 – List Ops: .append(), .remove() & direct edits. 02:53:35 – Joining: List concatenation via +. 02:55:02 – Tuples: Immutability & List-Conversion hack. 03:05:13 – Dictionaries: Key-Value (JSON) architecture. 03:13:42 – Dict Ops: .update(), .pop() & clearing data. 03:16:28 – Sets: Unordered unique items & .union(). 03:31:41 – NumPy: Performance Benchmark vs Lists. 03:41:16 – Arrays: 1D, 2D (Matrices) & 5D tensors. 03:50:50 – Array Ops: Reshaping & Random data generation. 03:55:07 – Pandas: Data Wrangling & DataFrame logic. 03:57:20 – Titanic EDA: CSV I/O implementation. 04:02:03 – Describe(): Statistical health audit (Mean, Min, Max). 04:10:48 – Feature Engineering: Column insertion & dropping. 04:18:49 – Data Cleaning: Mean Imputation for missing values. 04:26:09 – Matplotlib: Linear vs Zig-zag line plotting. 04:34:45 – Charts: Customizing vertical/horizontal Bar plots. 04:40:12 – Pie Charts: Visualizing categorical distribution. 04:41:42 – Seaborn: Statistical Data Visualization (SDV). 04:47:21 – Hue Parameter: Multi-categorical color coding. 04:55:00 – Distributions: Histograms & KDE Density plots. 04:58:38 – Capstone: Conversational Voice-AI prototype. 05:01:11 – Cloud Dev: Google AI Studio implementation. 05:05:51 – Local Dev: Coding Voice Assistant via Python. 05:06:58 – Integrations: Speech Recognition, pyttsx3 & Wiki-API. 05:08:33 – Execution: Live Q&A with Python-built Bot. 05:10:47 – Summary ✨ Kickstart your career in a Data Analyst. Apply today! - https://www.theiscale.com/DataAnalyti... ❇️ Explore our Job Oriented Courses: https://www.theiscale.com/explore-course ➖➖➖➖➖➖ 📱 For Any Further Query or Doubts? Contact- 7880-113-112 (Student Helpline Number) For any query connect in WhatsApp with us: https://wa.me/917880113112 ➖➖➖➖➖➖ ✳️ Join Telegram Channel- https://t.me/TheiScale ✳️ Join WhatsApp Channel- https://whatsapp.com/channel/0029VaB5... ➖➖➖➖➖➖➖ 🔗 Download App Google Play : https://play.google.com/store/apps/de...