OUR COURSES

Embark on a transformative 4-month online journey to become a proficient Machine Learning practitioner. This comprehensive program is designed to take you from foundational concepts to advanced techniques, equipping you with the in-depth knowledge and practical skills demanded by today's leading organizations.

Course Schedule: September to December, Mondays, Wednesdays, and Thursdays, 7:00 PM - 9:00 PM EDT.

Time Commitment: This is an intensive program designed for serious learners. To truly master the material and excel in the hands-on practice exercises, students should plan to devote 20-25 hours per week to the course, encompassing live online sessions, independent study, comprehensive project work, and thorough review of materials.

Valuable Benefit: Upon successful completion of the course, each student will receive one voucher for a Machine Learning Cloud Exam from either Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure. This significant benefit empowers you to pursue industry-recognized certification and validate your expertise to potential employers.

Major Topics Covered:

 * Fundamentals of Machine Learning:

   * Core concepts: data types, features, labels, models, training, validation, testing.

   * Understanding different learning paradigms: Supervised, Unsupervised, Reinforcement Learning.

   * Key applications across various industries.

 * Data Science Toolkit & Preprocessing:

   * Python for Machine Learning: NumPy, Pandas, Matplotlib, Seaborn.

   * Data Acquisition, Cleaning, and Transformation: Handling missing values, outliers, data inconsistencies.

   * Feature Engineering: Creating new features, feature scaling (standardization, normalization), encoding categorical variables.

   * Exploratory Data Analysis (EDA) for insightful data understanding.

 * Supervised Learning Algorithms (Foundational to Advanced):

   * Regression: Linear Regression (Simple, Multiple), Polynomial Regression, Regularization techniques (Ridge, Lasso, Elastic Net).

   * Classification: Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machines (SVM) with different kernels, Decision Trees, Ensemble Methods (Random Forests, Gradient Boosting - XGBoost, LightGBM, CatBoost).

 * Unsupervised Learning & Dimensionality Reduction:

   * Clustering: K-Means, Hierarchical Clustering, DBSCAN, Gaussian Mixture Models.

   * Dimensionality Reduction: Principal Component Analysis (PCA), t-SNE for visualization.

 * Model Evaluation, Selection & Optimization:

   * Comprehensive evaluation metrics for regression (MAE, MSE, RMSE, R-squared) and classification (Accuracy, Precision, Recall, F1-score, ROC-AUC).

   * Bias-Variance Trade-off, Overfitting, Underfitting.

   * Cross-validation strategies (K-Fold, Stratified K-Fold).

   * Hyperparameter Tuning: Grid Search, Random Search, Bayesian Optimization.

   * Model Interpretability: SHAP, LIME (Introduction).

 * Deep Learning Fundamentals & Architectures:

   * Introduction to Artificial Neural Networks (ANNs), Perceptrons, Multi-Layer Perceptrons (MLPs).

   * Activation Functions, Loss Functions, Optimizers.

   * Introduction to Convolutional Neural Networks (CNNs) for image data.

   * Introduction to Recurrent Neural Networks (RNNs) for sequential data.

   * Working with popular deep learning frameworks (TensorFlow/Keras, PyTorch).

 * Machine Learning Operations (MLOps) & Cloud Deployment:

   * Cloud Computing Essentials for ML: Scalability, resource management, cost optimization in a cloud environment.

   * Practical Cloud ML Platforms (GCP, AWS, Azure):

     * Utilizing managed ML services for data ingestion, model training, and deployment (e.g., AWS SageMaker, Google AI Platform/Vertex AI, Azure Machine Learning).

     * Version control for data and models.

     * Monitoring deployed models and ensuring performance.

     * Introduction to CI/CD for ML pipelines in the cloud.

The AWS Certified Cloud Practitioner offers a foundational understanding of AWS Cloud concepts, services, and terminology. This is a good starting point for individuals in non-technical roles with no prior IT or cloud experience or for those with on-premises IT experience looking for basic AWS Cloud fluency.

What You will learn: 

• The foundation of cloud computing
• The core AWS services, including computing, network, and storage 
• Security best practices and compliance in AWS Cloud 
• Basic understanding of IT services and their uses on AWS Cloud
• Knowledge of core AWS services and use cases, billing and pricing models, security concepts, and how cloud impacts your business.

AWS Certified Solutions Architect - Associate showcases knowledge and skills in AWS technology, across a wide range of AWS services. The focus of this certification is on the design of cost and performance optimized solutions, demonstrating a strong understanding of the AWS Well-Architected Framework. This certification can enhance the career profile and earnings of certified individuals and increase your credibility and confidence in stakeholder and customer interactions.

AWS Certified Solutions Architect is among the most valuable and sought-after cloud computing certifications in the world. We designed this cloud architect certification training for anyone seeking to learn the major components of Amazon Web Services (AWS). By the end of the course, you'll be prepared to pass the associate-level AWS Certified Solutions Architect certification exam.

We’ll start with a broad overview of the AWS platform. No programming knowledge is needed, and no prior AWS experience is required. Even if you have never logged in to the AWS platform before, you’ll build the foundations to pass the AWS Certified Solutions Architect exam after completing our certification training.

We know you’re busy, so our training course is made up of mix of live classes snd pre-recorded videos that can be viewed at your convenience. Our video lessons keep it simple, explaining things clearly and succinctly. Together, we’ll walk you through each of the major areas of Amazon Web Services, step by step. Using real-life examples, we will practice how to effectively design and manage application infrastructure using AWS. At the end of each section, we’ll also test your knowledge with short quizzes to make sure you’ll be ready for the exam.

Not only will we cover the fundamentals of AWS architectural principles and services, we will also dive into each of the individual elements: IAM, S3, CloudFront, Storage Gateway, Snowball, EC2, CloudWatch, CLI, Lambda, Route 53, RDS, DynamoDB, Redshift, ElastiCache, Aurora, VPC, SQS, SNS, Elastic Transcoder, Kinesis, API Gateway, and so on.

AWS is constantly evolving their platform. We will continuously update this course with new content so you will never have to worry about missing out or failing the AWS certification test because of new content.

The ideal student for this course is ready to quickly break into cloud computing. You don’t have hours to spend on training. We get you up to speed in half the time as other certification courses. The course will help you prepare for a position as a qualified AWS solutions architect.

At the end of this course, you’ll be able to confidently take the associate-level AWS Certified Solutions Architect exam!

With real-world projects and immersive content, you’ll master the tech skills that companies want.

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