Algorithmic Mastery with AI - Full Day
In today’s AI-powered era, mastering algorithms isn’t just about passing interviews — it’s about solving real-world problems with clarity, efficiency, and scale.
This workshop equips developers, architects, and technical leads with a 7-step framework for algorithmic problem-solving — enhanced by AI tools like ChatGPT and GitHub Copilot. Through hands-on coding, guided exercises, and AI-augmented decision-making, participants will learn to move from brute force to elegant, optimized solutions that scale.
Outcomes:
Confidence to solve problems with clarity and structure.
A personal toolkit of reusable algorithmic patterns.
Ability to use AI to accelerate problem-solving safely.
Practical experience connecting algorithms → systems.
A repeatable framework for tackling interviews and production challenges.
Audience:
Developers & Software Engineers (coding mastery).
Technical Architects (system-level optimization).
Engineering Leaders (mentorship, design reviews).
Net Result:
You leave not just as a better coder, but as an AI-empowered problem solver who can transform any problem into a systematic, optimized, and scalable solution.
Agenda:
Module 1: Foundations of Algorithmic Thinking
Why algorithms matter beyond interviews.
The 7-step problem-solving framework.
AI as partner, not crutch.
Mini-exercise: clarify → brute force → optimize.
Module 2: Arrays, Hashing & Sliding Window Techniques
Frequency maps, prefix sums, two pointers.
Fixed vs. variable window problems.
Hands-on: Longest substring without repeats.
AI demo: auto-generating edge cases.
Module 3: Trees, Recursion & Divide-and-Conquer
Binary trees, BSTs, traversals.
Recursion principles: base case design, stack depth.
Divide & conquer in search/sort.
Exercise: Subset generation with recursion.
AI support: spotting infinite recursion.
Module 4: Graph Algorithms in Action
BFS vs. DFS, cycle detection, topological sort.
Shortest path algorithms (Dijkstra, A*).
Real-world uses: routing, dependencies, scheduling.
Hands-on: Course prerequisite (DAG + cycle check).
Module 5: Dynamic Programming & Greedy Strategies
DP basics: overlapping subproblems, optimal substructure.
Memoization vs. tabulation.
Greedy wins vs greedy fails.
Exercise: Coin change → greedy vs DP.
AI demo: recurrence relation generation.
Module 6: Optimization & Complexity Awareness
From brute force → optimized solutions.
Time/space complexity refinement.
When to optimize, when not to.
Hands-on: optimizing rotated array search.
AI code review: spotting inefficiencies.
Module 7: System-Level Algorithmic Thinking
How algorithmic choices shape APIs & backend logic.
Readability, modularity, maintainability.
Scaling strategies: caching, sharding, parallelism.
Capstone exercise: build scalable recommendation logic.
AI for documentation + design alternatives.
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.