UCS538: Data Science Fundamental

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General Information

Teacher Code: PSR (Dr PS Rana) | GEK (Dr. Geeta Kasana) | ANK (Anika) | RA4 (Priya Arora) | RA15 (Sawinder Kaur)

Guidelines for Zoom meeting

  • Join/login with *@thapar.edu email id only.
    (You cannot join with other email id).

  • No entry after 5 min in the class.

Guidelines for Telegram Group

  • Click here to Join UCS538 telegram group

  • Click here to Join Krish Naik telegram group

  • Share blog, videos, internships or any other relevant info.

Theory Class

Lab Class

Only for Minor in CSE

Lab Class

Theory Class

Table of Content
 
1. Syllabus
 
2. Time Table
 
3. Lecture Slides
  • [23 Jul 2020  ] Day01 - Welcome to Data Science Fundamental
  • [24 Jul 2020  ] Day02 - Basics of Python, Syntax, Operators, Variable, if-else
  • [30 Jul 2020  ] Day03 - Loops, Functions, Math Library, Strings
  • [31 Jul 2020  ] Day04 - Random Number-String, Exception Handling
  • [06 Aug 2020] Day05 - Data Structures in Python - List
  • [07 Aug 2020] Day06 - Data Structures in Python - Dictionary
  • [13 Aug 2020] Day07 - Data Structures in Python - Tuple
  • [14 Aug 2020] Day08 - Data Structures in Python - Sets
  • [20 Aug 2020] Day09 - File Handling and Use of Lambda
  • [21 Aug 2020] Day10 - Command-line arguments and Call External Commands
  • [27 Aug 2020] Day11 - OOPs in Python - Part1 - Class, Object, Method
  • [10 Sep 2020] Day12 - OOPs in Python - Part2 - Inheritance, Overriding, Abstraction, Encapsulation
  • [11 Sep 2020] Day13 - Data Manipulation using Pandas - Part1 - Series and Data Frame
  • [17 Sep 2020] Day14 - Data Manipulation using Pandas - Part2 - Working with CSV
  • [18 Sep 2020] Day15 - Data Manipulation using Pandas - Part3 - Read JSON, HTML, Excel and Pickle files
  • [24 Sep 2020] Day16 - Data Visualization using Matplotlib
  • [25 Sep 2020] Day17 - Data Visualization using Seaborn
  • [01 Oct 2020 ] Day18 - Working with Numpy
  • [08 Oct 2020 ] Day19 - Data Generation using Modelling and Simulation
 
4. Lab Experiments
  • Lab01 - Python Installation, Google Colab, Github, Google Dataset Search, Kaggle, Anaconda
    • [Explore Video 1] Learn How to use Google Colab | Link1   Link2   Link3  Link4  Link5
    • [Explore Video 2] Learn How to use Github | Link1    Link2  
    • [Explore Web 1] Explore Google Dataset Search | Click Here
    • [Explore Web 2] Explore Kaggle (Compete, Datasets, Notebooks, Jobs, more) | Click Here
    • Download & Install Anaconda for Python | Click Here to download
      Default Editor → Spyder  |  To start python idle → Open "Anaconda Prompt" and write "idle"
    • Practice: Lecture of Day02 | Click Here
  • Lab02 - Basics of Python, Loops, Functions, String, Exception Handling
    • [Explore Video 1] How To Learn Data Science by Self Study and For Free | Click Here
    • [Explore Video 2 (imp)] How To Learn Data Science Smartly? | Click Here
    • [Explore Video 3] Role of Maths in Data Science | Click Here
    • [Explore Video 4] Step By Step Transition Towards Data Science | Click Here
    • [Explore Video 5] Complete Life Cycle of a Data Science Project | Click Here
    • [Explore Video 6] Step By Step Action Plan For Learning Data Science in 2020 | Click Here
    • Practice: Lecture of Day03 and Day04 | Click Here
  • Lab03 - Data Structures in Python (List, Dictionary)
    • [Explore Video 1 (imp)] Step By Step Playlist To Learn Data Science Through Kish Naik Channel Part 1 | Click Here
    • [Explore Video 2 (imp)] Step By Step Playlist To Learn Data Science Through Kish Naik Channel Part 2 | Click Here
    • Practice: Lecture of Day05 and Day06 | Click Here
  • Lab04 - Data Structures in Python (Tuple, Sets)
    • [Explore] Learn Neural Network and Deep Learning with code and Videos (By Prof Jeff Heaton) | Video  Code   
    • Practice: Lecture of Day07 and Day08 | Click Here
  • Lab05 - File Handling, Use of Lambda, Command-line arguments and Call External Commands
    • [Explore (imp)] Student Projects @ Stanford UniversityClick Here
    • [Explore (imp)] Student Projects @ MIT Click Here
    • Practice: Lecture of Day09 and Day10 | Click Here
    • Practice: How to read a file in Google Colab | Link1 Link2
  • Lab06 - OOPs in Python
    • [Explore (imp)] Student Projects @ LeadingIndia.ai Click Here
    • [Explore (imp)] Research Projects @ LeadingIndia.ai Click Here
    • [Explore (imp)] Resources @ LeadingIndia.ai Click Here
    • Practice: Lecture of Day11 and Day12 | Click Here
  • Lab07 - Data Manipulation using Pandas
    • [Explore Video (imp)] Data Manipulation using Pandas by Kish Naik | Part1  Part2  Part3
    • Practice: Lecture of Day13, Day14 and Day15 | Click Here
  • Lab08 - Data Visualization using Matplotlib and Seaborn
    • [Explore (imp)] PyPi.org: Python packages for research Click Here
    • [Explore (imp)] Two minutes Papers Click Here
    • [Explore (imp)] Papers With Code | Click Here
    • Practice: Lecture of Day15 and Day16 | Click Here
 
5. Assingments
Evaluation Criteria: Multiplying Factor (MF)
      Assignment_Marks = 10          # Lets assume
      if (Assignment_Submitted_Within_Due_Date):
                   MF = 1
      else:
                  MF = 1 - abs(Submission_Date - Due_Date)/10
 
      You_Get_the_Marks_From = Assignment_Marks * MF
5.1 A01 - Basics of Python | Due Date: 23 Aug 2020 | 23:59:59 | Assignment Link | Submission Link
5.2 A02 - File Processing | Due Date: 23 Aug 2020 | 23:59:59 | Assignment Link | Submission Link
5.3 A03 - Video Processing using OpenCV | Due Date: 06 Sep 2020 | 23:59:59 | Assignment Link | Submission Link
5.4 A04 - Merging of Results | Due Date: 20 Sep 2020 | 23:59:59 | Assignment Link | Submission Link
5.5 A05 - Feature Extraction | Due Date: 27 Sep 2020 | 23:59:59 | Assignment Link | Submission Link
 
 
6. Books
6.1 Python Data Science Handbook | Click Here
6.2 Book 1
6.3 Book 2
 
7. Projects
7.1 DNA Sequencing Classifier using Machine Learning (Notebook is available in the description) | Click Here
7.2 Colour Detection | Click Here
7.3 Titanic data exploration and prediction using Machine Learning | Click Here
7.4 Tumer Analysis (by Kritika Aggarwal) | Click Here
7.5 How To Train Deep Learning Models In Google Colab- Must For Everyone | Click Here
7.6 Handling Imbalanced Datasets   SMOTE Technique | Click Here
7.7 Tumer Analysis (by Kritika Aggarwal) | Click Here
 
8. Self Learning Resources
8.1 Explore and subscribe to Youtube Channels
8.2 Data Science Projects playlist | Click Here
8.3 Free Coursera Courses for Thapar Students | Click Here and Join with *@thapar.edu. Click on Catalog.
8.4 Learn NumPy in a very easy way (By Simran, BE, 4th Yr) | Click Here
8.5 Learn Neural Network and Deep Learning with code and Videos (By Prof Jeff Heaton) | Video  Code

 
9. Resource for Research Paper
9.1 Paper With Code | Click Here
9.2 Two Minutes Papers | Click Here
9.3 For Research Papers

Search using DOI (Digital Object Identifier) | Example (Search for): 10.1016/j.bbapap.2014.07.010

Search using title | Example (Search for): "Quality assessment of modeled protein structure using"

9.4 For Books
9.5 For Thesis
Student's Data Science Projects
 
1. Tumer Analysis (by Kritika Aggarwal, BE, 3rd yr) | Click Here
2. Learn NumPy in a very easy way (by Simran, BE, 4th yr) | Click Here
3. Instagram-Scrapper (by Parth Verma, BE, 3rd Yr) | Video  Code
4. Neural Network from Scratch in Python (by Tanmay Agarwal, BE, 3rd yr ) | Code
5. Comming Soon.....