4.1 Learning Objectives.mp4
4.2 Introduction to Linear Algebra.mp4
4.3 Scalars and vectors.mp4
4.4 Dot product of Two Vectors.mp4
4.5 Linear Independence of Vectors.mp4
4.6 Norm of a Vector.mp4
4.7 Matrix.mp4
4.8 Matrix Operations.mp4
4.9 Transpose of a Matrix.mp4
4.10 Rank of a Matrix.mp4
4.11 Determinant of a matrix and Identity matrix or operator.mp4
4.12 Inverse of a matrix and Eigenvalues and Eigenvectors.mp4
4.13 Calculus in Linear Algebra.mp4
4.14 Importance of Statistics for Data Science.mp4
4.15 Common Statistical Terms.mp4
4.16 Types of Statistics.mp4
4.17 Data Categorization and types of data.mp4
4.18 Levels of Measurement.mp4
4.19 Measures of central tendency mean.mp4
4.20 Measures of Central Tendency Median.mp4
4.21 Measures of Central Tendency Mode.mp4
4.22 Measures of Dispersion.mp4
4.23 Variance.mp4
4.24 Random Variables.mp4
4.25 Sets.mp4
4.26 Measure of Shape Skewness.mp4
4.27 Measure of Shape Kurtosis.mp4
4.28 Covariance and corelation.mp4
4.29 Basic Statistics with Python Problem Statement.mp4
4.30 Basic Statistics with Python Solution.mp4
4.31 Probability its Importance and Probability Distribution.mp4
4.32 Probability Distribution Binomial Distribution.mp4
4.33 Binomial Distribution using Python.mp4
4.34 Probability Distribution Poisson Distribution.mp4
4.35 Poisson Distribution Using Python.mp4
4.36 Probability Distribution Normal Distribution.mp4
4.37 Probability Distribution Uniform Distribution.mp4
4.38 Probability Distribution Bernoulli Distribution.mp4
4.39 Probability Density Function and Mass Function.mp4
4.40 Cumulative Distribution Function.mp4
4.41 Central Limit Theorem.mp4
4.42 Bayes Theorem.mp4
4.43 Estimation Theory.mp4
4.44 Point Estimate using Python.mp4
4.45 Distribution.mp4
4.46 Kurtosis Skewness and Student's T distribution.mp4
4.47 Hypothesis Testing and mechanism.mp4
4.48 Hypothesis Testing Outcomes Type I and II Errors.mp4
4.49 Null Hypothesis and Alternate Hypothesis.mp4
4.50 Confidence Intervals.mp4
4.51 Margin of Errors.mp4
4.52 Confidence Levels.mp4
4.53 T test and P values Using Python.mp4
4.54 Z test and P values Using Python.mp4
4.55 Comparing and Contrastin T test and Z tests.mp4
4.56 Chi Squared Distribution.mp4
4.57 Chi Squared Distribution using Python.mp4
4.58 Chi squared Test and Goodness of Fit.mp4
4.59 ANOVA.mp4
4.60 ANOVA Terminologies.mp4
4.61 Assumptions and Types of ANOVA.mp4
4.62 Partition of Variance.mp4
4.63 F distribution.mp4
4.64 F Distribution using Python.mp4
4.65 F Test.mp4
4.66 Advanced Statistics with Python Problem Statement.mp4
4.67 Advanced Statistics with Python Solution.mp4
4.68 Key Takeaways.mp4