verified_user
Target Output
Weekly Production Deliverable
Deliverable: Greedy done. You can explain what a neuron, a layer, activation functions, and gradient descent-for-NNs are, conceptually.
Monday
0 / 2 done
DSA
Assign Cookies; Lemonade Change
1.5h
AI/ML
Neural Networks Intuition 1
3Blue1Brown — Neural Networks, Ch.1 "But what IS a neural network?" & Ch.2 "Gradient descent, how neural networks learn" (visualizing high-dimensional loss landscapes, weight updates)
2.5h
Tuesday
0 / 2 done
DSA
Jump Game
I
1.5h
CORE
CN Foundations & Physical Media
Why Networks Exist, Network Types (LAN, WAN, MAN), Clients/Servers/Peers, How data moves in packets, Packet Switching vs Circuit Switching, Transmission Media (Twisted Pair, Fiber Optic Cable, Coaxial Cable), Full-Duplex vs Half-Duplex, Physical & Logical Topologies + Quiz
2.5h
Wednesday
0 / 2 done
DSA
Shortest Job First; Job Sequencing Problem
1.5h
AI/ML
Neural Networks Intuition 2
3Blue1Brown Ch.3 "What is backpropagation really doing?" & Ch.4 "Backpropagation calculus" (chain rule applied backwards through layers, partial derivatives)
2.5h
Thursday
0 / 2 done
DSA
N meetings in one room
1.5h
CORE
Layered Architecture: OSI & TCP/IP
Why Layered Architecture? OSI 7-layer model vs TCP/IP 4-layer model, Data encapsulation and decapsulation, Protocol Data Units (PDUs) at each layer + Quiz
2.5h
Friday
0 / 2 done
DSA
Non-overlapping Intervals; Insert Interval
1.5h
AI/ML
Deep Learning Foundations
StatQuest — "Neural Networks/Deep Learning" playlist: Activation functions (Sigmoid, Tanh, ReLU, Leaky ReLU), forward pass matrix operations, Cross-Entropy Loss vs MSE Loss
2.5h
⚡
Weekend High-Load Execution
• 8.0h Daily Deep Focus Lab
Saturday
0 / 3 done
DSA
Minimum number of platforms required
1.5h
AI/ML
Karpathy's micrograd Part 1 (4.0h)
Build scalar Value engine with computational graph and forward pass (
+, *, relu, pow).
4.0h
APT
Quant M16 & Verbal/Logical
Quant M16 Compound Interest (Basic & Advance) + Verbal/Logical Mixed Practice
2.5h
Sunday
0 / 3 done
DSA
Valid Parenthesis Checker; Candy + Contest + revision
1.5h
AI/ML
Karpathy's micrograd Part 2 & Backprop Ninja (4.0h)
Implement reverse-mode automatic differentiation (topological sort + backward pass); train a tiny 2-layer MLP on a toy dataset.
4.0h
APT
Physical & Data Link Layer
Transmission Media (Twisted pair, Fiber, Coaxial), MAC Address, Framing, Error Detection (CRC, Checksum), CSMA/CD, CSMA/CA, Address Resolution Protocol (ARP)
2.5h
edit_note
Week 16 Technical Notes & Journal
#LeetCode
#Java
#DSA
#Week16