description Description

Price‌ ‌-‌ ‌Paid:‌ 
7410‌ 
 
JobsForHer‌ ‌Offer:‌ 
0‌ 
 
Description:‌ 
If‌ ‌you‌ ‌want‌ ‌to‌ ‌break‌ ‌into‌ ‌competitive‌ ‌data‌ ‌science,‌ ‌then‌ ‌this‌ ‌course‌ ‌is‌ ‌for‌ ‌you!‌ ‌Participating‌ ‌in‌ 
predictive‌ ‌modelling‌ ‌competitions‌ ‌can‌ ‌help‌ ‌you‌ ‌gain‌ ‌practical‌ ‌experience,‌ ‌improve‌ ‌and‌ ‌harness‌ 
your‌ ‌data‌ ‌modelling‌ ‌skills‌ ‌in‌ ‌various‌ ‌domains‌ ‌such‌ ‌as‌ ‌credit,‌ ‌insurance,‌ ‌marketing,‌ ‌natural‌ 
language‌ ‌processing,‌ ‌sales’‌ ‌forecasting‌ ‌and‌ ‌computer‌ ‌vision‌ ‌to‌ ‌name‌ ‌a‌ ‌few.‌ ‌At‌ ‌the‌ ‌same‌ ‌time‌ 
you‌ ‌get‌ ‌to‌ ‌do‌ ‌it‌ ‌in‌ ‌a‌ ‌competitive‌ ‌context‌ ‌against‌ ‌thousands‌ ‌of‌ ‌participants‌ ‌where‌ ‌each‌ ‌one‌ ‌tries‌ 
to‌ ‌build‌ ‌the‌ ‌most‌ ‌predictive‌ ‌algorithm.‌ ‌Pushing‌ ‌each‌ ‌other‌ ‌to‌ ‌the‌ ‌limit‌ ‌can‌ ‌result‌ ‌in‌ ‌better‌ 
performance‌ ‌and‌ ‌smaller‌ ‌prediction‌ ‌errors.‌ ‌Being‌ ‌able‌ ‌to‌ ‌achieve‌ ‌high‌ ‌ranks‌ ‌consistently‌ ‌can‌ 
help‌ ‌you‌ ‌accelerate‌ ‌your‌ ‌career‌ ‌in‌ ‌data‌ ‌science.‌ 
 
In‌ ‌this‌ ‌course,‌ ‌you‌ ‌will‌ ‌learn‌ ‌to‌ ‌analyse‌ ‌and‌ ‌solve‌ ‌competitively‌ ‌such‌ ‌predictive‌ ‌modelling‌ ‌tasks.‌  
 
When‌ ‌you‌ ‌finish‌ ‌this‌ ‌class,‌ ‌you‌ ‌will:‌ 
 
-‌ ‌Understand‌ ‌how‌ ‌to‌ ‌solve‌ ‌predictive‌ ‌modelling‌ ‌competitions‌ ‌efficiently‌ ‌and‌ ‌learn‌ ‌which‌ ‌of‌ ‌the‌ 
skills‌ ‌obtained‌ ‌can‌ ‌be‌ ‌applicable‌ ‌to‌ ‌real-world‌ ‌tasks.‌ 
-‌ ‌Learn‌ ‌how‌ ‌to‌ ‌preprocess‌ ‌the‌ ‌data‌ ‌and‌ ‌generate‌ ‌new‌ ‌features‌ ‌from‌ ‌various‌ ‌sources‌ ‌such‌ ‌as‌ 
text‌ ‌and‌ ‌images.‌ 
-‌ ‌Be‌ ‌taught‌ ‌advanced‌ ‌feature‌ ‌engineering‌ ‌techniques‌ ‌like‌ ‌generating‌ ‌mean-encodings,‌ ‌using‌ 
aggregated‌ ‌statistical‌ ‌measures‌ ‌or‌ ‌finding‌ ‌nearest‌ ‌neighbors‌ ‌as‌ ‌a‌ ‌means‌ ‌to‌ ‌improve‌ ‌your‌ 
predictions.‌ 
-‌ ‌Be‌ ‌able‌ ‌to‌ ‌form‌ ‌reliable‌ ‌cross‌ ‌validation‌ ‌methodologies‌ ‌that‌ ‌help‌ ‌you‌ ‌benchmark‌ ‌your‌ ‌solutions‌ 
and‌ ‌avoid‌ ‌overfitting‌ ‌or‌ ‌underfitting‌ ‌when‌ ‌tested‌ ‌with‌ ‌unobserved‌ ‌(test)‌ ‌data.‌  
-‌ ‌Gain‌ ‌experience‌ ‌of‌ ‌analysing‌ ‌and‌ ‌interpreting‌ ‌the‌ ‌data.‌ ‌You‌ ‌will‌ ‌become‌ ‌aware‌ ‌of‌ 
inconsistencies,‌ ‌high‌ ‌noise‌ ‌levels,‌ ‌errors‌ ‌and‌ ‌other‌ ‌data-related‌ ‌issues‌ ‌such‌ ‌as‌ ‌leakages‌ ‌and‌ 
you‌ ‌will‌ ‌learn‌ ‌how‌ ‌to‌ ‌overcome‌ ‌them.‌  
 
 
 
 
-‌ ‌Acquire‌ ‌knowledge‌ ‌of‌ ‌different‌ ‌algorithms‌ ‌and‌ ‌learn‌ ‌how‌ ‌to‌ ‌efficiently‌ ‌tune‌ ‌their‌ 
hyperparameters‌ ‌and‌ ‌achieve‌ ‌top‌ ‌performance.‌  
-‌ ‌Master‌ ‌the‌ ‌art‌ ‌of‌ ‌combining‌ ‌different‌ ‌machine‌ ‌learning‌ ‌models‌ ‌and‌ ‌learn‌ ‌how‌ ‌to‌ ‌ensemble.‌  
-‌ ‌Get‌ ‌exposed‌ ‌to‌ ‌past‌ ‌(winning)‌ ‌solutions‌ ‌and‌ ‌codes‌ ‌and‌ ‌learn‌ ‌how‌ ‌to‌ ‌read‌ ‌them.‌ 
 
Disclaimer‌ ‌:‌ ‌This‌ ‌is‌ ‌not‌ ‌a‌ ‌machine‌ ‌learning‌ ‌course‌ ‌in‌ ‌the‌ ‌general‌ ‌sense.‌ ‌This‌ ‌course‌ ‌will‌ ‌teach‌ 
you‌ ‌how‌ ‌to‌ ‌get‌ ‌high-rank‌ ‌solutions‌ ‌against‌ ‌thousands‌ ‌of‌ ‌competitors‌ ‌with‌ ‌focus‌ ‌on‌ ‌practical‌ 
usage‌ ‌of‌ ‌machine‌ ‌learning‌ ‌methods‌ ‌rather‌ ‌than‌ ‌the‌ ‌theoretical‌ ‌underpinnings‌ ‌behind‌ ‌them.‌ 
 
Prerequisites:‌  
-‌ ‌Python:‌ ‌work‌ ‌with‌ ‌DataFrames‌ ‌in‌ ‌pandas,‌ ‌plot‌ ‌figures‌ ‌in‌ ‌matplotlib,‌ ‌import‌ ‌and‌ ‌train‌ ‌models‌ 
from‌ ‌scikit-learn,‌ ‌XGBoost,‌ ‌LightGBM.‌ 
-‌ ‌Machine‌ ‌Learning:‌ ‌basic‌ ‌understanding‌ ‌of‌ ‌linear‌ ‌models,‌ ‌K-NN,‌ ‌random‌ ‌forest,‌ ‌gradient‌ 
boosting‌ ‌and‌ ‌neural‌ ‌networks.‌ 
 
Duration:‌ ‌6‌ ‌weeks‌ 
 
 
Price:‌ ‌‌INR‌ ‌7410‌ 
 
JobsForHer‌ ‌Price:‌ ‌FREE‌  
 
By‌ ‌National‌ ‌Research‌ ‌University‌ ‌Higher‌ ‌School‌ ‌of‌ ‌Economics‌ 
 
Apply‌ ‌to‌ ‌this‌ ‌course‌ ‌now‌ ‌and‌ ‌stand‌ ‌a‌ ‌chance‌ ‌to‌ ‌win‌ ‌it‌ ‌for‌ ‌FREE!‌  
 
Hurry,‌ ‌last‌ ‌date‌ ‌is‌ ‌July‌ ‌25th!‌