Advanced Python with Machine Learning

COURSE OVERVIEW

Are you ready to elevate your Python programming skills to new heights and delve into the exciting world of machine learning? Our “Advanced Python Programming with Machine Learning” is offered online via Udemy and it is a comprehensive and hands-on learning experience that will equip you with the knowledge and tools to become a proficient Python programmer and machine learning practitioner. Moreover, you can 1-to-1 coaching from us.

COURSE HIGHLIGHTS

Mastering Python Fundamentals: This course starts by reinforcing your foundational Python skills and then takes you on a journey through advanced programming techniques. You’ll become a Python pro, proficient in object-oriented programming, data structures, and handling exceptions.
Data Handling and Manipulation: Learn to work with data effectively, using libraries like NumPy, Pandas, and Matplotlib. Discover how to preprocess and visualize data, essential skills for any data scientist or machine learning engineer.
Machine Learning Fundamentals: Delve into the core concepts of machine learning, including supervised and unsupervised learning, classification, regression, clustering, and more. Understand the theory behind machine learning algorithms and their practical applications.
Hands-on Coding Projects: Apply your newfound knowledge in real-world projects. You’ll work on a variety of machine learning tasks, such as image recognition, natural language processing, and predictive modeling, which will sharpen your coding skills and build your portfolio.
Advanced Libraries and Frameworks: Explore powerful machine learning libraries such as Scikit-Learn and TensorFlow. Gain the expertise needed to implement machine learning models and neural networks efficiently.
Model Evaluation and Optimization: Understand how to assess the performance of your machine learning models and fine-tune them for optimal results. Dive into cross-validation, hyperparameter tuning, and feature selection techniques.
Practical Applications: Discover how machine learning is used in real-world applications, from healthcare and finance to recommendation systems and autonomous vehicles. Explore the latest trends and developments in the field.
Industry-Ready Skills: Infoclub Ltd’s instructors, who are experienced professionals in the field, will guide you through industry best practices, enabling you to be well-prepared for a career in data science, machine learning, or software development.

1. Introduction to AI and Machine Learning

Understanding AI, machine learning, and their applications
Overview of supervised, unsupervised, and reinforcement learning
Case Studies in machine Learning
Ethical Issues in Machine Learning

2. Foundations of Machine Learning with Python

Stages in a Machine Learning project
Data preprocessing and cleaning
Exploratory data analysis (EDA) with Python libraries
Feature engineering and selection
Model evaluation metrics and techniques

3. Supervised Learning Algorithms

Linear regression and regularization techniques
Python programs to do linear regression
Practical exercises using Python libraries
Model evaluation and accuracy.
Deployment

4. Classification problems

Decision trees and ensemble methods (Random Forest, Gradient Boosting)
Support Vector Machines (SVM)
Python programs to do linear classification
Confusion matrix
Model evaluation and accuracy. Deployment

5. Unsupervised Learning and Clustering

K-Means clustering
Hierarchical clustering
Dimensionality reduction techniques (PCA, t-SNE)
Applying clustering to real-world datasets

6. Neural Networks and Deep Learning

Introduction to neural networks
Building and training feedforward neural networks using TensorFlow/Keras
Convolutional Neural Networks (CNN) for image recognition
Recurrent Neural Networks (RNN) for sequence data

7. Advanced Topics and Project Presentations

Reinforcement learning concepts
Hyperparameter tuning and model optimization
Ethical considerations in AI and machine learning

AI PROJECT

(Each participant will do at least 1 project below or alternate)

Image Classification with Convolutional Neural Networks (CNN): Develop an image classification model using CNNs to classify images into different categories. Use dataset CIFAR-10 or a custom dataset related to a specific domain.
Sentiment Analysis and Chatbot Integration: Build a sentiment analysis model using Azure Text Analytics to classify user feedback from social media or a website as positive, negative, or neutral. Then, integrate this model with a chatbot using Azure Bot Service to respond contextually.
Predictive Analytics with Azure Machine Learning: Create a predictive model using Azure Machine Learning Studio to forecast trends or outcomes in a specific domain, such as stock prices or customer behavior. Deploy the model and build a web app to showcase predictions in real-time.

COURSE ORGANISATION

We have created an online program with a large set of hands-ons labs.

BENEFITS OF THIS COURSE

There are many benefits in becoming a Pro Python Programmer

In-Demand Skillset: Machine learning and Python programming are highly sought-after skills in today's job market. Completing this course equips you with expertise in both areas, making you a valuable asset to employers in various industries.

Career Advancement: Whether you're looking to enter the field of data science, enhance your current role, or transition to a new career, this course provides you with the knowledge and skills needed to advance your career in technology and data-driven industries.

Hands-On Experience: The course emphasizes practical, hands-on learning. Through real-world projects and coding assignments, you gain valuable experience that can be directly applied in your job or future projects.

Comprehensive Curriculum: The course covers a wide range of topics, from mastering Python fundamentals to advanced machine learning concepts. You'll acquire a well-rounded education, ensuring you're well-prepared for the challenges of the field.

STUDENT REGISTRATION

Once you have completed this form, please contact us or come on site to complete the registration process.