Krish Naik's Statistics in Machine Learning: study plan and how long it takes
The Krish Naik playlist is 44 videos and 23.9 hours long. Here's how long it takes at different paces, a week-by-week schedule built from the real videos, and a planner that turns it into your own daily plan.
44 videos · 23.9 hours · Krish Naik
Krish Naik's statistics playlist covers what data scientists need: distributions, random variables, correlation, p-values, confidence intervals, sampling, hypothesis testing, covariance and correlation, plus live sessions on statistics with Python and a complete six-hour statistics course.
It's oriented towards data science interviews as much as theory.
Who it's for: Aspiring data scientists preparing for interviews who want statistics explained with Python examples.
How long does it take?
The full playlist is 23.9 hours across 44 videos. Here's roughly how many days that is at different daily watch times and speeds, counting video time only:
| Daily time | At 1x | At 1.5x | At 2x |
|---|---|---|---|
| 30 min a day | 48 days | 32 days | 24 days |
| 1 h a day | 24 days | 16 days | 12 days |
| 2 h a day | 12 days | 8 days | 6 days |
Make your own schedule
The playlist link is already filled in. Press Plan, set how much time you have each day and your speed, and you'll get a day-by-day schedule with a finish date and a calendar file. It reads the live playlist, so new videos are included.
Week-by-week schedule
A sample plan at 1 hour a day and normal speed, using whole videos so none is split across days. That's 3 weeks in total. For a different pace, start date or speed, use the planner above.
Week 1Videos 1–29 · 5h 53m
Day 1 · 55m
- 1How to Learn Statistics for Data Science As A Self Starter- Follow My Way20m
- 2Introduction To Statistics And Its Types For Starters10m
- 3Population vs Sample in Statistics13m
- 4Gaussian distribution or Normal Distribution in statisctics12m
Day 2 · 57m
- 5Log Normal Distribution in Statistics16m
- 6Covariance in Statistics12m
- 7STATISTICS- Mean, Median And Mode Explained Easily8m
- 8STATISTICS- Population VS Sample and it's Importance10m
- 9STATISTICS- What are Random Variables and It's Types and its Importance?7m
- 10STATISTICS- Gaussian/ Normal Distribution5m
Day 3 · 48m
- 11STATISTICS- What is Central Limit Theorem?5m
- 12STATISTICS- Chebyshev's InEquality5m
- 13Statistics- What is Pearson Correlation Coefficient? Difference between Correlation and Covariance11m
- 14Spearman's rank correlation coefficient- Statistics11m
- 15Statistics-Finding Outliers in Dataset using Z- score and IQR16m
Day 4 · 50m
- 16Standardization Vs Normalization- Feature Scaling13m
- 17What Is P Value In Statistics In Simple Language?11m
- 18Statistics-Left Skewed And Right Skewed Distribution And Relation With Mean, Median And Mode7m
- 19Stats Interview Series #1- Asked In Interview2m
- 20Stats Interview Series #2-Asked In Interview2m
- 21Confidence Intervals In Statistics- Part 115m
Day 5 · 49m
- 22Bernoulli distribution- Mean, Variance And Standard Deviation OF Bernoulli distribution12m
- 23Stats Interview Series #3-Asked In Interview #shorts⭐ ⭐⭐⭐⭐⭐⭐⭐1m
- 245 Number Summary And How To handle Outliers Using IQR-Statistics16m
- 25Different Type Of Sampling Techniques With Examples| Statistics Interview Question9m
- 26Whether We Should Reduce False Positive Or Negative In Confusion Matrix-Machine Learning Interviews11m
Day 6 · 22m
- 27Z Score And Its Applications- Important Stats Interview Question12m
- 28Power Law Distribution And Its Examples And Application- Statistics Interview Question10m
Day 7 · 1h 11m
- 29How To Perform Hypothesis Testing-Confidence Interval|Z Test Statistics| Derive Conclusion- Part 11h 11m
Week 2Videos 30–39 · 8h 55m
Day 8 · 46m
- 30All Important Topics In Probability For Data Science In 1 Video27m
- 31Permutation And Combination Easily Explained10m
- 32Why Sample Variance is Divided by n-19m
Day 9 · 35m
- 33Covariance,Pearson Correlation And Spearman Correlation Coefficient With Real World Examples34m
- 34We Use Stats Everywhere!!1m
Day 10 · 1h 29m
- 35Live Day 1- Introduction To statistics In Data Science1h 29m
Day 11 · 1h 26m
- 36Live Day 2- Basic To Intermediate Statistics1h 26m
Day 12 · 1h 35m
- 37Live Day 3- Intermediate Statistics With Python In Data Science1h 35m
Day 13 · 1h 31m
- 38Live Day 4- Advance Statistics With Python In Data Science1h 31m
Day 14 · 1h 32m
- 39Live Day 5- Advance Statistics With Python In Data Science1h 32m
Week 3Videos 40–44 · 9h 9m
Day 15 · 1h 39m
- 40Live Day 6- Advance Statistics With Python In Data Science1h 39m
Day 16 · 1h 21m
- 41Live Day 7- Summarizing Statistics With Python In Data Science1h 21m
Day 17 · 21m
- 42How To Calculate P Value In Hypothesis Testing21m
Day 18 · 5h 29m
- 43Complete Statistics For Data Science In 6 hours By Krish Naik5h 29m
Day 19 · 20m
- 44Watch This Video To Crack Any Stats Interview For Data Scientist- Understanding PDF,PMF and CDF20m
Tips for finishing
- The six-hour complete statistics video overlaps with the shorter tutorials. Watch one or the other and tick off the rest in the playlist length calculator.
- Save the final interview video for the week before your interviews.