C Programming from Scratch to Master

Explore bit manipulation basics with left shift, bitwise and masking, and bitwise or merging, and learn how binary representation and powers of two enable efficient data operations.

Learn three methods to find duplicates in a string, including a hash table counting approach and bit manipulation with ascii offsets, left shifts, and masking, plus time and space analysis.

Explore recursion by defining it, examining base conditions, and tracing function calls, while understanding stack memory, time complexity, and recurrence relations.

Trace recursion with a tree and activation records to visualize calls on the stack, and analyze time and space using recurrence relations and ascending/descending phases.

Demonstrates solving recurrence relations using successive substitution, identifying base conditions, and distinguishing homogeneous from non-homogeneous cases, with three examples and their time complexities.

Learn to solve recurrence relations by forming the characteristic equation and converting to a quadratic. Determine constants A and B from two base conditions, then assess time complexity.

Apply successive substitution to solve three recurrence relations, derive base conditions, and conclude time complexities such as log base two of n and n log base two of n.

Analyze time complexity from recurrence relations and graphs, comparing constant, logarithmic, linear, linear-log, quadratic, and exponential costs to evaluate recursive algorithms.

Explore indirect recursion through step-by-step function calls, activation records, and base conditions, while tracing prints and analyzing time complexity with log base two.

Learn to solve recurrence relations for indirect and nested recursion with successive substitution and tracing in the C programming context, and understand why nested recursion is unstable and discouraged.

Explore tree recursion in C programming by tracing a function that prints values and recurses twice with n-1, examining base conditions, stack frames, and exponential time complexity.

Learn to compute the sum of natural numbers with recursion, including the base case sum(0)=0 and descending calls. Compare recursive, looping, and formula approaches, analyzing time and space complexity.

Explore factorial in C via recursion, using base case 0! = 1 and N! = N multiplied by (N minus 1)!, then compare with a loop.

Explore computing m^n via recursion with base case n=0 and recurrence n-1, multiplying by m. Compare recursive and loop methods and apply divide-and-conquer exponentiation for logarithmic time.

Explore recursion to implement the Taylor series for e^x, building powers and factorials with a base case and summing terms up to n to approximate e^x.

Explore an optimized recursive approach to Taylor series in C, using static variables to reuse powers and factorials, reducing time complexity from the previous method.

Explore recursive evaluation of the Taylor series for e^x, then apply optimization method 2 to reduce multiplications and time complexity, comparing three approaches and highlighting constant space and overall efficiency.

Explore the fibonacci series and its recursive implementation in c, starting from 0 and 1, deriving the fib formula F(n)=F(n-1)+F(n-2) with base cases, and analyzing time complexity and potential optimizations.

the lecture shows optimizing fibonacci series by replacing excessive recursion with memorisation and dynamic programming, and introduces benitz formula as a fast, space-efficient shortcut.