We are seeking candidates for Applied Machine Learning and Generative AIApplied ML and Gen AI Boot Camp Candidate Requirements:1. Basic Oops2. Data Structures3. Advanced Math- Statistics, Algebra,4. Excel for data manipulation and visualization5. Database and SQL6. Computer Science/Engineering BackgroundFoundational Knowledge (Prerequisite): 2 weeks· Basic Python - Variables, Data Types, Loops, Conditional Statements, functions, classes, file handling, exception handling, etc.· Mathematics & Statistics:· Linear Algebra· Descriptive Statistics - Measure of central tendency (Mean, Median, Mode), Measure of dispersion (variance, standard deviation)· Inferential Statistics - Hypothesis testing, correlation, covariance, Z-test, t-test, ANOVA test, etc.· Probability - Central limit theorem, Probability distribution, bayes theorem etc.Data Analysis and Preparation (Exploratory Data Analysis): 1 week· Data Handling and Manipulation using Numpy, Pandas, Scipy.· Data Visualization using Matplotlib, Seaborn, Google Data Studio· Feature engineering like imputing null values, handling outliers, scaling data.Project: Data Analysis of any business use case with complete visualization and conclusion. E.g. Uber case analysis.Machine Learning: 2 weeks· Introduction to frameworks like Scikit-Learn.· Supervised Learning· Introduction to both Regression and Classification problems.· Train models using algorithms like Linear regression, logistic regression, Decision tree, random forest, SVC, KNN, etc.· Evaluating models using metrics like RMSE, MAE, MSE, R2, accuracy, precision, recall, confusion matrix, F1-score etc.· Unsupervised Learning· Introduction to Clustering and Dimensionality Reduction problems.· Learn unsupervised algorithms like K-Means, PCA, LDA, etc.· Performance metrics like Elbow method, Silhouette CoefficientProjects:· Regression - use cases like house price prediction, etc.· Classification - use cases like email spam or not, etc.· Unsupervised - use cases like anomaly detection, etc.Deep Learning: 1 week· Introduction to frameworks like Tensorflow, Keras for Deep Learning.· What are Neural Networks and how do they function as the core of deep learning?Django (Framework for API integrations): 1 week· Django Basics like creating projects, django views, mapping urls.· Django Models to perform CRUD operations.· Database operationsProject: Creating REST API to perform all CRUD operations with MySQL Database.Generative AI: 2 week· Prompt Engineering· Data Privacy - Context, Domain· Best Practices- Token and Request optimization, Data Privacy considerations· Tools - ChatGPT, Vertex AI, Dall-E2, GitHub Copilot, etc.Project: Generate Job Description, Policy generation, etc.MLOps: 1 week· Model Deployment using Cloud based platforms like GCP, Azure, etc.· Testing Models and Data Pipelines· ML Pipelines and ML workflows.· Best Practices- cloud cost, Optimization of models· GCP/Azure creating and deploying models, configuring VMs /GPU,· Project : Install ML solution to GCP/Azure and update test data and rerun modelsElective Skills: 1 week· Natural Language Processing: Dealing text data using NLTK, spacy framework. Introduction to algorithms like Lemmatization, stemming, NER, Word2Vec, etc.· Computer Vision: Dealing with image data using OpenCV, PIL.Capstone Project: 2 week· Implement all the module learning and knowledge in a project like career coach, chatbot system, etc.OutcomeCertification: AZURE AI Fundamentals,Qualified for the roles of : ML Engineer, Data Engineer,Please contact to enroll @ 732 - 837 - 0242