A Series of 6-weeks in-depth machine learning workshops!
Kick-start your Data Science journey by this 6-weeks 6-weekends long series of Machine Learning for Data Science workshops specifically designed to teach the foundation concepts behind the buzz that is Data Science today.
learn by doing
Hands-on in-lecture coding tasks and assignments developed, in the most in-demand programming language Python, categorically to solidify the concepts learned.
constructive feedback from instructors
Get your assignments and class tasks evaluated by instructors along with the feedback to improve your Data Science skills.
Starting from 08th FEBruary
EVERY SATURDAY - 10 AM TO 4 PM
Pre-requisites
PROFICIENCY IN LOGIC PROGRAMMING
Should be proficient in logic building skills & computer programming constructs like Variables, Conditionals, Loops, etc.
SOUND KNOWLEDGE OF OOP & DATA STRUCTURES
Sound familiarity with Object Oriented Programming concepts and be able to correctly use Data Structures in code e.g. Lists, Arrays, Dictionaries, etc.
FUNDAMENTAL MATHEMATICAL PROFICIENCY
Familiarity with Linear Algebra, Probability & Statistics, & Calculus.
"A hands-on perspective without mathematics" is a dangerous myth!
Workshops outline
DS Weekends by Pakistan.AI - Machine Learning for Data Science
Week 1 - Intro To Python for Data Science
Defining Python for Data Science
Python Data Structures
Functions & Classes
NumPy Basics
Advanced NumPy Computations
Pandas Basics
Advanced Data Manipulation with Pandas
Assignment # 1
Week 2 - Bayesian classification methods
Reviewing Prior & Posterior Probabilities
Naive Bayes Classification
Full Bayes Classification
Text Data Preprocessing - BoW, N-grams, Word Embeddings, Stop Words Removal
Splitting Data Into Train, Validation & Test Data Sets
Cross validation & Hyper Parameter Tuning for N - grams
Precision, Recall, Accuracy & F1 Score
Assignment # 2
Week 3 - K - Nearest NEIGHBOR classifier & Regressor
KNN Classifier
KNN Regressor
Distance Metrics For Numerical & Categorical Data
Feature Scaling
Effects of Distance Metrics on Decision Boundary
Concept of lazy learners in ML
Overfitting & Underfitting KNN Models
Cross validation & Hyper Parameter Tuning To Choose Optimal Value of K
Bias and Variance Trade-off
Assignment # 3
Week 4 - Decision Trees & Random forests
Measuring Entropy & Information Gain
Decision Tree Classifier For Numerical Data
Decision Tree Classifier For Categorical Data
Regression through "variance in reduction" in decision trees
Visualizing decision tree boundary
Pruning a tree
Decision Trees Overfitting & Underfitting
Cross validation & Hyper Parameter Tuning for Depth & Purity
Motivation for Random Forests Vs Decision Trees
Random Forest As Bagging Algorithm
Defining Random Patches
Random Forest Overfitting & Underfitting
Cross validation & Hyper Parameter Tuning for Number of Trees, Depth & Purity
Assignment # 4
week 5 - Perceptron, SVM & Logistic Regression
Perceptron as Linear Binary Classifier
Logistic Regression As Linear Binary Classifier
Cross Entropy Loss
SVM Motivation and Maximizing of Margin
Regularization Techniques To Avoid Over Fitting
Assignment # 5
Week 6 - Regression Models & project discussion
Classification VS Regression Models
Evaluation Metrics - Accuracy VS Loss Functions
Gradient Descent Algorithm
Linear Regression & Curve Fitting
Underfitting & Overfitting Regression Models
Cross validation & Hyper Parameter Tuning for Degree of Polynomial
Ridge & Lasso Regression (classical examples of regularized learning algorithms)
Feature Selection with Lasso Regression
Penalizing Weight To Counter Overfitting
Assignment # 6
Project Details
A note on ML best practices
Kaggle Project Discussion
Where To Go From Here!
Project
REGISTRATION process
Register for DS-Weekends - Machine Learning for Data Science here.
Keep an eye out for follow-up application process email from us. Complete the steps mentioned in that email.
Wait for our selection confirmation email.
AISHA JAVED
Chapter Lead @
Pakistan.AI - Isb
AI Engineer @
DPS UnternehmerTUM GmbH
MUNEEBA SIRSHAR
Academic Trainer @ Pakistan.AI - Isb
D.S. Corporate Trainer @ AMZ Consulting Pty Ltd
ABEER NOOR
Academic Trainer @ Pakistan.AI - Isb
Software Engineer @ Emumba Pvt Ltd
SAAD ZIA
Academic Trainer @ Pakistan.AI - Isb
Research Scientist @ Automotive AI (GmbH)
Venue
frequently asked questions
Who should attend these workshops?
We encourage both professionals & students to apply who want to either kick-start their Data Science careers or compliment their existing roles with Data Science knowledge. The pre-requisites as mentioned above referring to Proficiency in Logic Programming, Sound Knowledge of OOP & Data Structures & Fundamental Mathematical Proficiency are bare minimum!
What are the timings and duration of the workshops?
The 6 weeks workshops will be held on Saturdays from 10 am to 4 pm starting from 08th February, 2020.
Will I receive a certificate after successfully completing this course?
Yes, on successful completion of this series of workshops, you will be given certificate of completion by Pakistan.AI