| S.No |
Topic |
Sub-Topics |
| 1 | Introduction | Overview, Installation, NumPy array, Differences with list, np.array() |
| 2 | Array Basics | 1D array, 2D array, 3D array, ndim, shape |
| 3 | Array Creation | arange, zeros, ones, linspace, eye |
| 4 | Data Types | dtype, astype, type promotion, itemsize, kind |
| 5 | Indexing & Slicing | Indexing, Slicing, Negative indexing, Steps, Multi-dimensional indexing |
| 6 | Fancy Indexing | Integer indexing, Boolean indexing, mask arrays, where(), nonzero() |
| 7 | Array Operations | Arithmetic ops, Universal functions (ufunc), Broadcasting, Aggregation, Comparisons |
| 8 | Advanced Operations | sum, mean, std, min, max, argmin, argmax |
| 9 | Reshaping Arrays | reshape, flatten, ravel, transpose, swapaxes |
| 10 | Stacking & Splitting | vstack, hstack, concatenate, split, vsplit, hsplit |
| 11 | Broadcasting Advanced | Rules, Shape compatibility, Example, Broadcasting in ufunc, Arithmetic operations |
| 12 | Copy vs View | Shallow copy, Deep copy, view(), copy(), memory layout |
| 13 | Random Module | rand, randint, randn, seed, shuffle |
| 14 | Mathematical Functions | sqrt, exp, log, sin, cos, tan |
| 15 | Linear Algebra Basics | dot, matmul, transpose, inv, det, eigh |
| 16 | Statistical Functions | mean, median, var, std, percentile, correlation |
| 17 | Sorting & Searching | sort, argsort, argmax, argmin, searchsorted |
| 18 | Polynomials | poly1d, roots, polyval, fit, coefficients |
| 19 | Set Operations | unique, intersect1d, union1d, setdiff1d, in1d |
| 20 | String Operations | char module, vectorized string ops, split, join, replace |
| 21 | Masked Arrays | ma.masked_array, masking condition, compress, filled, mask |
| 22 | Structured Arrays | dtype definition, field access, record array, indexing, slicing |
| 23 | Time Series | datetime64, timedelta64, date arithmetic, frequency conversion, indexing |
| 24 | Fourier Transform | fft, ifft, rfft, irfft, frequency analysis |
| 25 | Memory Layout | C order, F order, strides, contiguous array, copy flags |
| 26 | Vectorization | Loop elimination, ufuncs, broadcasting, efficient computation, np.einsum |
| 27 | Advanced Indexing | fancy indexing, boolean masks, ix_, combine indexing, multi-dimensional selection |
| 28 | Integration with Pandas | Convert to DataFrame, from DataFrame, NumPy arrays in pandas, indexing, calculations |
| 29 | Performance Tips | Vectorization, memory layout, dtype optimization, broadcasting, avoiding loops |
| 30 | End-to-End Project | Data loading, cleaning, analysis, linear algebra, visualization |
