CD201
CodeDocs Course 201
Register
Date and Timings Will be updated soon.
Syllabus :
This course is oriented to teach you and help you learn
Web Development,
Android Development,
Data Science,
Graphic Designing,
and other essential and relevant skills needed for any path.
Topics include algorithms, data structures, resource management, cloud, software engineering, Data Science, web and android development.
Languages include
HTML, CSS, JavaScript, Database, Serve and Client side scripting,
GIT version control system,
Linux Session,
Android Studio
,
etc. Problems sets and assignments are inspired from basic domains.
The course is designed for every rank of student (any branch, semester).
Expectations :
You are expected to:
- attend all the lectures or classes
- submit the final project
- take at least one test or quiz
- bring your own laptop
- it would be better if you have any Linux OS
Grades or Scores :
The final grades or scores will be based on your problems sets and final test and project.
Books :
We will post links to referred books (purchase and free pdf) here soon.
Video Tutorials:
the links will be added soon.
Lectures:
There would be 8-9 lectures, each of around 60-70 minutes twice a week. The classes will be taught by CodeDocs team only, no other lecturer or trainer would join.
Web Development
Lecture
Topics
Lecture 0
Getting started with the HTML
Lecture 1
CSS - Styling the Web s
Lecture 2
Responsive Web Design
Lecture 3
JavaScript Fundamentals
Lecture 4
Client-side scripting
Lecture 5
Server Side Scripting
Lecture 6
Introduction to CRUD
Lecture 7
Working with database.
Lecture 8
Introduction to frameworks, libraries and essential tools
Android Development
Lecture
Topics
Lecture 0
Getting started with Android and Android architecture
Lecture 1
Basics of JAVA
Lecture 2
Setting up Android SDK and First Project
Lecture 3
Building a basic Android app,layouts
Lecture 4
Activities and Intents
Lecture 5
Connect to the internet (JSON and more)
Lecture 6
UI of Android & preferences
Lecture 7
Data Storage in Android - SQLite
Lecture 8
Firebase, RecyclerView & Fragments
Lecture 9
Android APIs
Data Science with Python!
Lecture
Topics
Lecture 0
Python Express : Basics of Python to kickstart Data Science
Lecture 1
Data Analysis Part 1 : Intro to NumPy, Pandas
Lecture 2
Data Analysis Part 2 : DA w/ Numpy and Pandas
Lecture 3
Data Visualisation Part 1 : DV w/ MatPlotLib, Seaborn(½)
Lecture 4
Data Visualisation Part 2 : DV w/ Searborn(2/2), pandas built in dv
Lecture 5
Data PreProcessing Track Rev : Rev and Intro to PlotLy, Cufflinks
Lecture 6
ML Intro Track Part 1SL1 : Supervised Learning, Linear Regression, Logistic Regression [Basics]
Lecture 7
ML Intro Track Part 2SL2 : CV Set, Bias-Variance,Regularization
Lecture 8
ML Intro Track Part 3 : ML System Design, Precision Recall
Lecture 9
ML Intro Track Part 4 UL : Unsupervised Learning, K-Means Clustering, PCA,Intro To Recommender System
Graphic Designing
Lecture
Topics
Lecture 0
Introduction to Photoshop Tools
Lecture 1
Layer Blending Modes
Lecture 2
Layer mask and photo manupulation
Lecture 3
Light, Shadow and subject adjustments
Lecture 4
Retouching, Sharpaning effects with advance tools
Lecture 5
Adobe Illustrator: Intorduction to Illustrator tools
Lecture 6
Drawing and making basic structures
Extra
Lecture
Topics
Lecture 0
Git and Github
Lecture 1
Linux Session
Lecture 2
UI & UX
Office hours:
We will conduct office hours every week for 1-2 hours where you can ask and get your problems solved with us. And we will help you with hands-on on your project.
Problem sets:
Problem sets with basic webpages, Data Science and android activities will roll out with every class and has to be done before next class.
Final Project:
The climax of this course is its final project. The final project is your opportunity to take your newfound savvy with programming out for a spin and develop your very own piece of software. So long as your project draws upon
this course’s lessons, the nature of your project is entirely up to you. You can choose your own final project or also help solving college's problems and building for college or other Open Source organization.
Test or Quiz:
2-3 test will be conducted for you to map your progress and compete in standings. We will try bringing you some goodies.
Suggestions:
If you have any suggestions or queries, feel free to raise an issue.
Star the repository, and watch it to stay updated with Problem Sets and Notes
Syllabus :
This course is oriented to teach you and help you learn Web Development, Android Development, Data Science, Graphic Designing, and other essential and relevant skills needed for any path. Topics include algorithms, data structures, resource management, cloud, software engineering, Data Science, web and android development. Languages include HTML, CSS, JavaScript, Database, Serve and Client side scripting, GIT version control system, Linux Session, Android Studio , etc. Problems sets and assignments are inspired from basic domains. The course is designed for every rank of student (any branch, semester).
Expectations :
You are expected to:
- attend all the lectures or classes
- submit the final project
- take at least one test or quiz
- bring your own laptop
- it would be better if you have any Linux OS
Grades or Scores :
The final grades or scores will be based on your problems sets and final test and project.
Books :
We will post links to referred books (purchase and free pdf) here soon.
Video Tutorials:
the links will be added soon.
Lectures:
There would be 8-9 lectures, each of around 60-70 minutes twice a week. The classes will be taught by CodeDocs team only, no other lecturer or trainer would join.
Web Development
| Lecture | Topics |
|---|---|
| Lecture 0 | Getting started with the HTML |
| Lecture 1 | CSS - Styling the Web s |
| Lecture 2 | Responsive Web Design |
| Lecture 3 | JavaScript Fundamentals |
| Lecture 4 | Client-side scripting |
| Lecture 5 | Server Side Scripting |
| Lecture 6 | Introduction to CRUD |
| Lecture 7 | Working with database. |
| Lecture 8 | Introduction to frameworks, libraries and essential tools |
Android Development
| Lecture | Topics |
|---|---|
| Lecture 0 | Getting started with Android and Android architecture |
| Lecture 1 | Basics of JAVA |
| Lecture 2 | Setting up Android SDK and First Project |
| Lecture 3 | Building a basic Android app,layouts |
| Lecture 4 | Activities and Intents |
| Lecture 5 | Connect to the internet (JSON and more) |
| Lecture 6 | UI of Android & preferences |
| Lecture 7 | Data Storage in Android - SQLite |
| Lecture 8 | Firebase, RecyclerView & Fragments |
| Lecture 9 | Android APIs |
Data Science with Python!
| Lecture | Topics |
|---|---|
| Lecture 0 | Python Express : Basics of Python to kickstart Data Science |
| Lecture 1 | Data Analysis Part 1 : Intro to NumPy, Pandas |
| Lecture 2 | Data Analysis Part 2 : DA w/ Numpy and Pandas |
| Lecture 3 | Data Visualisation Part 1 : DV w/ MatPlotLib, Seaborn(½) |
| Lecture 4 | Data Visualisation Part 2 : DV w/ Searborn(2/2), pandas built in dv |
| Lecture 5 | Data PreProcessing Track Rev : Rev and Intro to PlotLy, Cufflinks |
| Lecture 6 | ML Intro Track Part 1SL1 : Supervised Learning, Linear Regression, Logistic Regression [Basics] |
| Lecture 7 | ML Intro Track Part 2SL2 : CV Set, Bias-Variance,Regularization |
| Lecture 8 | ML Intro Track Part 3 : ML System Design, Precision Recall |
| Lecture 9 | ML Intro Track Part 4 UL : Unsupervised Learning, K-Means Clustering, PCA,Intro To Recommender System |
Graphic Designing
| Lecture | Topics |
|---|---|
| Lecture 0 | Introduction to Photoshop Tools |
| Lecture 1 | Layer Blending Modes |
| Lecture 2 | Layer mask and photo manupulation |
| Lecture 3 | Light, Shadow and subject adjustments |
| Lecture 4 | Retouching, Sharpaning effects with advance tools |
| Lecture 5 | Adobe Illustrator: Intorduction to Illustrator tools |
| Lecture 6 | Drawing and making basic structures |
Extra
| Lecture | Topics |
|---|---|
| Lecture 0 | Git and Github |
| Lecture 1 | Linux Session |
| Lecture 2 | UI & UX |
Office hours:
We will conduct office hours every week for 1-2 hours where you can ask and get your problems solved with us. And we will help you with hands-on on your project.
Problem sets:
Problem sets with basic webpages, Data Science and android activities will roll out with every class and has to be done before next class.
Final Project:
The climax of this course is its final project. The final project is your opportunity to take your newfound savvy with programming out for a spin and develop your very own piece of software. So long as your project draws upon this course’s lessons, the nature of your project is entirely up to you. You can choose your own final project or also help solving college's problems and building for college or other Open Source organization.
Test or Quiz:
2-3 test will be conducted for you to map your progress and compete in standings. We will try bringing you some goodies.
Suggestions:
If you have any suggestions or queries, feel free to raise an issue.