Machine Learning Training by Mr. Vimal Daga
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Python Bootcamp - Session 1: CPU Performance | Polyglot Programming | Installing Anaconda | REPL | Statements | RAM | OS | Interpreters | Kernel | Variables | Data Types | Integers | Boolean | Float | Strings | f-String | Arrays | Tuples | CRUD | Lists | Operators | Loops (463:00)
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Summary Python Bootcamp Session 1
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Summary Python Bootcamp Session 2
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Summary Python Bootcamp Session 3
OOPs (Object-Oriented Programming) concepts Session By Mr. Vimal Daga
Data Structure & Algorithms (DSA) with Mr. Vimal Daga
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Session 1 - Concurrent users | Traffic patterns | Scalability | Server limits | Automation | System design | Tsunami effect | Infra mgmt | Problem-solving | Performance optimization | Full-stack dev | DevOps | SRE | ML | MLOps | GenAIOps | DevSecOps | Efficiency | Resource & time optimization | (118:53)
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Summary Session 1
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Session 2 - Data structures | Algorithms | Optimization | Profit | Resource mgmt | Time complexity | Big O | Algorithmic thinking | Pseudo code | Programming | Worst-case | Constant time | Problem-solving | Efficiency | Scalability | Performance | Cost reduction | Automation | System design (134:23)
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Summary Session 2
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Session 3 - Problem-solving | Algorithm | Runtime | RAM | CPU | Servers | Optimization | Space Complexity | Time Complexity | Efficiency | Cost | Performance | Execution | Process | Resources | Function | Analysis | Solid Principle | Modularity | Compute Device (125:10)
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Summary Session 3
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Session 4 - Algorithms & Functions | Time Complexity (Big O) | Loops in Python (Iteration & Recursion) | Using range() in for loops | Efficient Programming | Constant Time O(1) | Variable Time O(n) | Resource Planning (Hotstar Example) | Time Complexities (O(1), O(n), O(n²)) | Problem-Solving (140:34)
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Summary Session 4
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Session 5 - Natural Number Sum | Real-world Problem Mapping | Identifying Patterns | Loop Implementation | Pseudocode Writing | Variable Naming | Time Complexity (Big O) | Function Optimization | Jupyter Magic Commands | Arithmetic Progression Formula (116:13)
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Summary Session 5
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Session 6 - Algorithmic Thinking | Iteration vs. Recursion | Function Design & Modularity | Direct & Indirect Recursion | Base Conditions in Recursive Functions (111:46)
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Summary Session 6
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Summary Session 7
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Summary Session 8
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Summary Session 9
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Summary Session 10
