Lectures

Week	Topic(s)	Slide(s)	Additional Resources
Week I 21.02	Chapter 9 - GUI Programming Using Tkinter Chapter 15 - GUI and Event Driven Programming	Ch 9: ppt | pdf Ch 9: html	Python GUI Examples (Tkinter Tutorial)  (html) Python Tkinter (html) Python - GUI Programming (Tkinter) (html) Introduction To GUI With Tkinter In Python (html) Tkinter Tutorial For Beginners (html) Tkinter tutorial - zetcode (html)
Week II 28.02	Chapter 13 - Files and Exception Handling Chapter 11 - Files	Ch 13: ppt | pdf Ch 11: html	w3schools - File Handling (html) programiz - File I/O (html) w3schools - Try Except (html) programiz - Exception Handling (html)
Week III 07.03	Chapter 15 - Recursion Chapter 16 - Recursion	Ch 15: ppt | pdf Ch 16: html	programiz - Recursion (html) realpython (html)
Week IV 14.03	Chapter 16 - Developing Efficient Algorithms [Liang] Chapter 3 - Analysis - Problem Solving with Algorithms and Data Structures using Python [Interactive Edition]	Ch16 : ppt | pdf Ch 03 : html
Week V 21.03	Chapter 17 - Sorting [Liang] Chapter 6 - Searching and Sorting - Problem Solving with Algorithms and Data Structures using Python [Interactive Edition] Chapter 11-  Computer Science Thinking: Recursion, Searching, Sorting and Big O [Deitel]	Ch17 : ppt | pdf Ch 06 : html Ch 11: html
Week V 21.03	IPython, Jupyter Notebooks, Review of Python Data Types and  Structures, and Libraries IPython: Beyond Normal Python¶ Help and Documentation in IPython Keyboard Shortcuts in the IPython Shell IPython Magic Commands Input and Output History IPython and Shell Commands Errors and Debugging Profiling and Timing Code More IPython Resources - Review of Python Data Types and Stuctures (html) - Python Libraries (html)		- Jupyter Notebook Tutorial: The Definitive Guide (html) - A Beginner's Tutorial to Jupyter Notebooks(html) - Jupyter Notebook: An Introduction (html) - Jupyter Notebook Users Manual (html) - 28 Jupyter Notebook Tips, Tricks, and Shortcuts (html) - Getting started with conda (html) - A gallery of interesting Jupyter Notebooks (html)
Week VI	Arrray-Oriented Programming with NumPy (html) Introduction to NumPy Understanding Data Types in Python The Basics of NumPy Arrays Computation on NumPy Arrays: Universal Functions Aggregations: Min, Max, and Everything In Between Computation on Arrays: Broadcasting Comparisons, Masks, and Boolean Logic Fancy Indexing Sorting Arrays Structured Data: NumPy's Structured Arrays		- tutprialspoint NumPy Tutorial (html) - Datacamp Python Numpy Array Tutorial (html) - The Ultimate Beginner’s Guide to NumPy (html) - A Complete Step-By-Step Numpy Tutorial (html)
Week VII	Quiz
Week VIII	Midterm Week
Week IX & X	Data Manipulation with Pandas¶ Introducing Pandas Objects Data Indexing and Selection Operating on Data in Pandas Handling Missing Data Hierarchical Indexing Combining Datasets: Concat and Append Combining Datasets: Merge and Join Aggregation and Grouping Pivot Tables Vectorized String Operations Working with Time Series High-Performance Pandas: eval() and query() Further Resources		- Pandas Pandas Tutorial: A Complete Introduction for Beginners (html) - EuroScipy 2016 Pandas Tutorial (html) - w3resource Pandas Tutorial(html) - Tutorialspoint Pandas turorial (html) - Java T point Pandas Tutorial (html) - geeksforgeeks Padas Tutorial (html)
Week XI	Ramadan Holiday
Week XII	- Ch 06 - Data Loading, Storage, and File Formats - Wes McKinney  (html) - Ch 08 - Strings - A Deeper  Look - Deitel (html) - Ch 09 - Files and Exceptions (html) - Primer on Python Decorators (html) - Decorators in Python (html)		- The Best Format to Save Pandas Data (html) - Pandas: How to Read and Write Files (html) - Loading Data Into A Pandas Dataframe - A Performance Study  (html) - How to read most commonly used file formats in Data Science (using Python)? (html) - Importing Data into Pandas (html) - Pandas IO tools (text, CSV, HDF5, ...)  (html) - A Guide to the Newer Python String Format Techniques (html) - Common string operations (html)
Week XIII	- Matplotlib Usage Guide (html) - Tutorialpoint- matplotlib Tutorial (html) Ch 04 - Visualization with Matplotlib - DS Handbook    - Introduction 04.00 (html) Ch 10 - Review of OO Programming,            - operator overloading,            - names tuples            - data classes            - unit testing - doctest            - Time Series and Simple Linear Regression (html)		- 6 Essential Data Visualization Python Libraries - Matplotlib, Seaborn, Bokeh, Altair, Plotly, GGplot (html) - Tutorial: Comparing 7 Tools For Data Visualization in Python (html) - matplolib.prg tutorials (html)
Week XIV	Ch 12 - Natural Language Processing (NLP) (html)		- TextBlob: Simplified Text Processing (html) - Natural Language Processing for Beginners: Using TextBlob (html) - Introducing TextBlob (html) - spaCy (html) - spaCy 101: Everything you need to know (html) - spaCy Tutorial to Learn and Master Natural Language Processing (NLP) (html) - Natural Language Processing With spaCy in Python (html) - Textatistic (html)
Week XV	Introduction to Classification, Regression and Clustering Ch 15 - Machine Learning: Classification, Regression and Clustering (html)		- scikit-learn Machine Learning in Python (html) - Introduction to k-Nearest Neighbors: A powerful Machine Learning Algorithm (with implementation in Python & R) (html) - K Nearest Neighbors - Classification (html) - KNN Algorithm - Finding Nearest Neighbors (html) - Model Validation Techniques (html) - Regression Algorithms - Overview (html) - Commonly used Machine Learning Algorithms (html) - K-Means (html) - The Most Comprehensive Guide to K-Means Clustering You’ll Ever Need (html) - Dimensionality Reduction Algorithms: Strengths and Weaknesses (html) - Choosing the right estimator (html)
Week XV	Chapter 16 - Deep Learning (html)		- Deep Learning Tutorial (html) - A Guide to Deep Learning by YN (html) -CNN Tutorial (html)
Week XVI	Chapter 17 - Big Data: Big Data: Hadoop, Spark, NoSQL and IoT (html)		- Big Data & Analytics Tutorials (html) - Big Data Hadoop Tutorial (html) - NoSQL Databses (html) - Apache Spark Tutorial (html) - What is Big Data (html)

 

Grades

   - Grades (html)