NOBIGDEAL TRAINING CENTRE CODING AND MACHING LEARNING CURRICULUM

 

 This is Focusing on foundational topics in software development, web development, and Python programming, including practical projects and assignments.

S/N	Day	Topic	Contents
1	Day One	Software Development	1. What is Software Development?<br>2. How Software Development works<br>3. Software needed for software development<br>4. Introduction to website using coding<br>5. How to create and edit an HTML page<br>6. Introduction to Tags and Elements<br>7. Basic HTML structure<br>8. Difference between Tag and Element<br>9. How to write HTML Tags and Elements<br>10. HTML Tags and functionality
2	Day Two	List Tag	1. Anchor link<br>2. Ordered list<br>3. Unordered list
3	Day Three	Table	1. What is a Table?<br>2. Table Structure<br>3. How to use Tables in a webpage
4	Free Day	Project 1	1. Create a simple webpage using HTML
5	Free Day	Project 2	1. Create two web pages and link them together
WEEK TWO
S/N	Day	Topic	Contents
1	Day One	Advanced Table	1. Designing Tables<br>2. Table Layout
2	Day Two	Form	1. What is a form?<br>2. How to use forms<br>3. Advanced forms
3	Day Three	CSS	1. Introduction to CSS<br>2. Types of CSS<br>3. Selectors<br>4. External CSS practice example
4	Free Day	Project 1	1. Design a simple layout using HTML & CSS<br>2. Design a calculator layout using HTML & CSS
5	Free Day	Project 2	1. Create a simple form<br>2. Create a simple form using a table layout
WEEK THREE
S/N	Day	Topic	Contents
1	Day One	Advanced Attributes	1. Introduction to Attributes and Values<br>2. Typesetting<br>3. Color<br>4. Background color and image
2	Day Two	Border, Margin, and Padding	1. What is a border and its functionalities?<br>2. What is padding and its functionalities?<br>3. What is margin and its functionalities?
3	Day Three	Form	1. Introduction to Class and ID Selectors<br>2. Form attributes and values
4	Free Day	Project 1	1. Type a formal letter using HTML and CSS<br>2. Design a letterhead using CSS
5	Free Day	Project 2	1. Create a webpage with a Navbar
WEEK FOUR
S/N	Day	Topic	Contents
1	Day One	JavaScript	1. Introduction to JavaScript<br>2. How to use JavaScript with HTML<br>3. Types of rules<br>4. Variable declaration and assigning<br>5. Introduction to Functions<br>6. How functions work
2	Day Two	Conditional Statement & Loop	1. IF Statement<br>2. For loops<br>3. While loops<br>4. Do...while loops
3	Day Three	Array	1. What is an Array?<br>2. Creating arrays<br>3. How to assign a value to an array<br>4. Accessing array values<br>5. Adding items to an array<br>6. Removing items from an array<br>7. Finding items in an array<br>8. Merging arrays
4	Free Day	Project 1	1. Design a calculator layout using HTML and CSS
5	Free Day	Project 2	1. Design a simple registration and login form
WEEK FIVE
S/N	Day	Topic	Contents
1	Day One	Object in JavaScript	1. What is an Object in JS?<br>2. How it works<br>3. Some Pre-defined JavaScript Objects<br>4. Date object
2	Day Two	DOM / Event	1. What is a DOM Function?<br>2. Events
3	Day Three	Classwork	1. Write a code to sum 10 consecutive numbers
4	Day Four	Project 1	1. Build a Stopwatch with HTML, CSS, and JavaScript
5	Day Five	Project 2	1. Build a student grading site
WEEK SIX
S/N	Day	Topic	Contents
1	Day One	WordPress	1. Introduction to WordPress<br>2. What is WordPress?<br>3. WordPress dashboard and log-in<br>4. WordPress themes and plugins
2	Day Two	Domain	1. What is a domain?<br>2. Types of domains<br>3. How to get a domain name<br>4. Getting your first domain
3	Day Three	Hosting	1. What is hosting?<br>2. Importance of hosting<br>3. How to host a site
4	Day Four	Project	1. Create and host your first website
5	Day Five	Project	1. Create an E-Commerce website
WEEK SEVEN
S/N	Day	Topic	Contents
1	Day One	Python	1. Introduction to Computer Programming<br>2. Installation of Python<br>3. Syntax of a computer programming language<br>4. Introduction to Python
2	Day Two	Python	1. Variable in Python<br>2. Variable declaration and assigning<br>3. Data types<br>4. Operators<br>5. Python tokens<br>6. Python keywords<br>7. Python identifiers
3	Day Three	Data Types	1. Literals<br>2. Strings<br>3. Data structures<br>4. Tuple
4	Day Four	Assignment	1. Print out 10 students' biodata
5	Day Five	Assignment	1. Sum five numbers using Python
WEEK EIGHT
S/N	Day	Topic	Contents
1	Day One	Function	1. What is a function?<br>2. How to define and use functions
2	Day Two	Data Structure	1. List<br>2. Dictionary<br>3. Set
3	Day Three	OOP in Python	1. What is an Object?<br>2. How to create an Object<br>3. What is a Class?<br>4. How to create a Class<br>5. Object and parameters<br>6. Creating a Class with a constructor<br>7. Inheritance
4	Day Four	Assignment	1. Create an object with any class of your choice
5	Day Five	Assignment	1. Create an array that sums two numbers
WEEK NINE
S/N	Day	Topic	Contents
1	Day One	Django	1. What is a web framework?<br>2. Why Django web framework?<br>3. Installing Django<br>4. Checking Django version
2	Day Two	Requirements	1. Downloading or upgrading Python<br>2. Checking the version<br>3. Pip installation<br>4. Code editor
3	Day Three	Creating First App	1. How to create directories<br>2. How to navigate to the directories created<br>3. Creating a virtual environment<br>4. Activating the environment<br>5. Installing Django
4	Day Four	Project	1. Creating your first project<br>2. Creating directories for the project<br>3. Start app project using your text editor<br>4. Adding the new app to the settings<br>5. Run the Django app on the server
WEEK TEN - PROJECT WEEK
S/N	Day	Topic	Contents
1	Day One	Project	1. To-do list app project
2	Day Two	Project

 

 

MACHINE LEARNING CURRICULUM

Week	Topic	Description	Key Concepts/Activities
1	Introduction to Machine Learning	Overview of machine learning, types, and applications.	- Types of ML (Supervised, Unsupervised, Reinforcement)<br>- Applications in various industries<br>- Basic Python libraries for ML (NumPy, Pandas, scikit-learn)
2	Data Preprocessing and Exploration	Techniques for preparing and exploring data for machine learning.	- Data cleaning<br>- Handling missing values<br>- Data normalization and standardization<br>- Exploratory Data Analysis (EDA)
3	Supervised Learning: Regression	Introduction to regression models and their applications.	- Linear regression<br>- Polynomial regression<br>- Model evaluation metrics (MSE, RMSE, R²)
4	Supervised Learning: Classification	Understanding classification algorithms and their use cases.	- Logistic regression<br>- Decision trees<br>- k-Nearest Neighbors (k-NN)<br>- Model evaluation metrics (accuracy, precision, recall, F1-score)
5	Unsupervised Learning	Introduction to clustering and dimensionality reduction techniques.	- k-Means clustering<br>- Hierarchical clustering<br>- Principal Component Analysis (PCA)
6	Deep Learning Basics	Introduction to neural networks and deep learning concepts.	- Neural networks<br>- Activation functions<br>- Introduction to TensorFlow/Keras<br>- Building a simple neural network
7	Convolutional Neural Networks (CNNs)	Understanding CNNs and their applications in image processing.	- Convolutional layers<br>- Pooling layers<br>- Building a simple CNN for image classification
8	Recurrent Neural Networks (RNNs)	Introduction to RNNs and their use in sequential data.	- RNN architecture<br>- Long Short-Term Memory (LSTM) networks<br>- Applications in time series and text data
9	Real-Life Model Development and Optimization	Developing machine learning models for real-world applications and optimizing performance.	- Model selection and tuning<br>- Cross-validation<br>- Hyperparameter optimization<br>- Avoiding overfitting and underfitting
10	Building AI-Powered Chatbots without Programming	Introduction to chatbot development using no-code/low-code platforms.	- Overview of chatbot platforms (e.g., Dialogflow, Botpress)<br>- Designing conversation flows<br>- Integrating pre-built AI models<br>- Practical exercise: Building a chatbot
11	Capstone Project: Proposal and Planning	Planning and proposing a capstone project to apply learned concepts.	- Project proposal and scope<br>- Data collection and preprocessing plan<br>- Model selection and evaluation criteria
12	Capstone Project: Development and Implementation	Building and implementing the capstone project.	- Model training and testing<br>- Performance evaluation<br>- Iteration and refinement
13	Capstone Project: Optimization and Finalization	Finalizing the project with optimization techniques and preparing for presentation.	- Model optimization<br>- Final testing<br>- Project documentation and presentation preparation
14	Capstone Project Presentation and Review	Presenting the capstone project and receiving feedback.	- Project presentation<br>- Q&A session<br>- Feedback and reflection