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Machine Learning

Avanteia Courses Course Details
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Machine Learning: Level-02

(1,230 reviews)
author
Created by
Avanteia

Total Enrolled

12,580

Last Update

15 September 2024

Category

Machine Learning

Introduction to Machine Learning: level-02

Overview:

  • Master deep learning, NLP, and scalable ML systems. Build real-world AI solutions for domains like healthcare, finance, and IoT.
  • Duration: 3 Months

Topics Covered:

  • Deep learning architectures: CNNs, RNNs, GANs
  • Natural language processing and computer vision
  • Advanced model tuning and regularization techniques
  • Deployment of machine learning models in production
  • Ethics and bias in machine learning

Syllabus

Module 1: Introduction to Machine Learning
  • What is ML? Types (Supervised, Unsupervised, Reinforcement)
  • ML vs AI vs Deep Learning
  • Real-world applications
  • ML workflow & pipeline

LAB 1
  • Install Python & Jupyter/Colab
  • Run a basic ML pipeline on Iris dataset in Scikit-learn

Module 2: Python for Machine Learning
  • Python essentials (functions, OOP, file handling)
  • NumPy, Pandas for data manipulation
  • Matplotlib, Seaborn for visualization

LAB 2
  • Load CSV dataset in Pandas
  • Perform summary statistics
  • Plot graphs using Matplotlib/Seaborn

Module 3 : Data Preprocessing & Feature Engineering
  • Data cleaning (missing values, outliers)
  • Categorical encoding (One-hot, Label Encoding)
  • Scaling (MinMax, StandardScaler)
  • Feature selection & extraction

LAB 3
  • Handle missing values in Titanic dataset
  • Apply feature scaling on dataset in Scikit-learn

Module 4 : Probability & Statistics for ML
  • Probability basics, Bayes Theorem
  • Distributions (Normal, Bernoulli, Binomial, Poisson)
  • Hypothesis testing (t-test, chi-square)

LAB 4
  • Simulate coin toss & dice using Python
  • Test significance using SciPy

Module 5 : Supervised Learning – Regression Models
  • Linear Regression, Multiple Regression
  • Polynomial Regression
  • Regularization (Lasso, Ridge)

LAB 5
  • Predict house prices using Linear Regression (Kaggle dataset)
  • Compare Ridge vs Lasso regression

Module 6 : Supervised Learning – Classification Models
  • Logistic Regression
  • k-Nearest Neighbors (k-NN)
  • Decision Trees
  • Support Vector Machines (SVM)

LAB 6
  • Predict Titanic survival (Logistic Regression)
  • Build k-NN classifier on Iris dataset

Module 7 : Ensemble Methods & Model Optimization
  • Random Forest, Gradient Boosting, XGBoost
  • Bagging vs Boosting vs Stacking
  • Hyperparameter tuning (GridSearchCV, RandomSearchCV)

LAB 7
  • Use Random Forest on loan prediction dataset
  • Perform hyperparameter tuning with GridSearch

Module 8 : Unsupervised Learning
  • k-Means Clustering
  • Hierarchical Clustering
  • PCA & Dimensionality Reduction

LAB 8
  • Perform customer segmentation using K-Means (Retail dataset)
  • Apply PCA on Wine dataset

Module 9 : Neural Networks & Deep Learning
  • Basics of Neural Networks
  • Forward & Backward Propagation
  • Activation functions
  • Introduction to TensorFlow & PyTorch

LAB 9
  • Build a simple ANN in TensorFlow/Keras
  • Classify MNIST digits

Module 10 : Advanced Deep Learning (CNNs & RNNs)
  • Convolutional Neural Networks (CNNs) for image recognition
  • Recurrent Neural Networks (RNNs), LSTMs for sequences
  • Transfer Learning basics

LAB 10
  • Build CNN for CIFAR-10 image classification
  • Train RNN for text prediction

Module 11 : Natural Language Processing (NLP)
  • Text preprocessing (tokenization, stemming, lemmatization)
  • Word embeddings (Word2Vec, GloVe, BERT basics)
  • Sentiment analysis

LAB 11
  • Build sentiment analysis model using NLTK & Scikit-learn
  • Use pre-trained BERT for text classification in HuggingFace

Module 12 : Model Deployment & Capstone Project
  • ML model deployment techniques
  • Flask & Streamlit for deployment
  • ML on Cloud (Google Colab, Streamlit Cloud, HuggingFace Spaces)

LAB 12
  • Deploy a classification model on Streamlit Cloud
  • End-to-End project: Choose dataset → Clean → Train → Deploy


Learning Outcome

  • Master advanced machine learning techniques, build complex models for NLP and computer vision, and deploy them in real-world applications while considering ethical issues.

Internship: Free internship opportunity included (Duration: 3 months)

Reviews

  • image
    Mansi Manjrekar
    August 12, 2024

    Avanteia offers the best IT courses in Goa! I enrolled for Digital Marketing and my friend joined Web Development – both of us got hands-on training with real projects. Highly recommend for job-seekers and students!

  • image
    Tanraj Simones
    March 10, 2024

    This is the only institute in Goa that truly focuses on career growth. Whether it's Cybersecurity, Blockchain or Digital Marketing, the trainers are super helpful and the learning is very practical.

  • image
    Barkelo Gaonkar
    July 19, 2024

    Avanteia Courses are industry-ready and job-focused. I loved the practical sessions, internship support, and certifications. If you're in Goa and serious about IT skills, this is the place to join.

Write a Review
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  • Level
    Level-02
  • Modules
    12
  • Duration
    3 Months
  • Category
    Machine Learning
  • Language
    English
  • Certificate
    Yes
Enroll Now

🛣️ Machine Learning Roadmap for Level 2 (Advanced)

Master machine learning by diving deep into advanced algorithms, model optimization, deployment strategies, and real-world applications.

1
Step 1
🚀

Machine Learning Level 02

Master advanced ML algorithms, optimization, big data integration, and deploy machine learning models at scale.

View Syllabus
2
Step 2
🧑‍💻

Internship

Apply advanced ML knowledge in real-world projects during a free 1-year internship, gaining valuable industry experience.

1 Year
FREE
3
Step 3
📝

Mini Project

Complete guided projects showcasing your expertise in large-scale machine learning and data science applications.

6 Months
4
Step 4
💼

Expected Jobs

Target senior roles like Lead ML Engineer, Data Science Manager, AI Consultant, and Research Scientist.

Lead ML Engineer
Data Science Manager
AI Consultant
Research Scientist
ML Architect
🎯

🏆 Career Destinations

Entry-level (India)
₹5–10 LPA
Mid-level (India)
₹12–25 LPA
Senior-level (India)
₹35–60 LPA+
🌎 Global Roles
$90,000–$180,000

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