CONTACT FOR DEMO CLASS : (+91) 8951869553/52
CONTACT FOR DEMO CLASS : (+91) 8951869553/52
Course Start Date: 20th January 2025
Participants will gain hands-on experience with Essential ML algorithms, learn to build predictive models, and understand how to integrate ML into software applications.
Understand the math and logic behind Essential algorithms like Linear Regression, Decision Trees, and K-Means Clustering.
Learn to clean, normalize, and transform raw data into a format suitable for training highly accurate machine learning models.
Master techniques for testing model performance using metrics like accuracy, precision, recall, and F1-score to ensure reliability.
Dive deep into the differences between learning paradigms and when to apply each to solve real-world problems effectively.
In this specialized session, developers and aspiring data scientists will dive into the foundational concepts of Machine Learning. The micro session covers Essential ML workflows, from understanding data types and feature engineering to training and evaluating supervised and unsupervised models.
Participants will explore popular ML libraries, learn to visualize data patterns, and understand the lifecycle of an ML project. By the end of this session, you will have a clear understanding of how ML algorithms work, how to prepare data for training, and how to choose the right model for your specific software engineering challenges.
EarlyRise's Machine Learning Fundamentals for Developers Micro Session Key Features
Build and train ML models from scratch
Master data preprocessing and feature selection
Understand the math behind popular ML algorithms
Evaluate model performance with real-world data
Apply ML to solve software engineering problems
Future-proof your career as an AI-enabled Developer
Customized to your team's needs
Key Learning Objective: Understanding the ML lifecycle, types of learning, and common terminology.
Key Learning Objective: Handling missing values, encoding categorical data, and feature scaling.
Key Learning Objective: Master Linear Regression, Logistic Regression, and Decision Trees.
Key Learning Objective: Using Cross-Validation and Hyperparameter tuning for optimization.
Key Learning Objective: Identifying hidden patterns and grouping data without labels.
Key Learning Objective: Simplifying complex datasets with PCA (Principal Component Analysis).
Key Learning Objective: Basic architecture of Artifical Neural Networks (ANNs).
Key Learning Objective: Serving model predictions via an API using Flask or FastAPI.
4 Hours
4 Hours
Upon successful completion of the course, participants will receive a certificate from EarlyRise. This certificate is widely recognized and signifies that the holder has acquired specialized skills and knowledge in Machine Learning Fundamentals for Developers. It serves as a testament to their expertise and is valued by industry professionals and employers.
Get In Touch
Our team will be happy to assist you make the right decision
Leading industry professionals who bring current best practices and case studies to sessions that fit into your work schedule.
Our Course fees are very nominal and competitive. We provide Scholarship up to 50% time to time for eligible candidates.
This session is ideal for software developers, engineers, and technical professionals who want to transition into or understand the core components of Machine Learning without getting bogged down in heavy theory.
No. We focus on the practical application and intuition of ML algorithms. While there is some math involved, we simplify it for developers, focusing on how to use tools and libraries like Scikit-Learn effectively.
You will be able to perform data preprocessing, train basic supervised and unsupervised models, evaluate their performance, and deploy a simple ML model as an API.
The session primarily uses Python, NumPy, Pandas, and Scikit-Learn. We also touch upon Flask and FastAPI for model deployment.
Yes. Participants get access to a resource kit containing code snippets, cheat sheets for ML algorithms, and a project template to jumpstart their ML journey.
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