Machine Learning Course & Certification
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Earn certification from EduCADD THINKWorks, India’s most trusted educational institution with over 25+ years of excellence, in collaboration with Mindforge and the National Skill Development Corporation (NSDC). Pursue a high-paying career in Machine Learning with Mindforge Infotech’s new Machine Learning Course and gain a competitive edge in the job market
The Machine Learning Course is designed to introduce participants to the core concepts and techniques used in building intelligent systems that learn from data. This course covers key topics such as supervised and unsupervised learning, regression, classification, clustering, and decision trees, along with advanced methods like neural networks and deep learning. Students will learn how to use popular machine learning libraries like Scikit-learn, TensorFlow, and Keras, and apply algorithms to real-world datasets. Through hands-on projects, participants will gain practical experience in building predictive models and deploying machine learning solutions in various domains.
In addition to the technical aspects, the course emphasizes understanding the ethical considerations and best practices for model evaluation, tuning, and interpretation. By the end of the course, students will have a strong foundation in machine learning, enabling them to solve complex problems using data-driven approaches. This training prepares individuals for careers in data science, AI development, and analytics, offering valuable skills in industries like finance, healthcare, marketing, and technology, where machine learning is increasingly critical for innovation and decision-making.
Machine Learning curriculum
- Overview of Machine Learning
- Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning
- Key Concepts: Features, Labels, Training, Testing, and Validation
- Applications of Machine Learning in Various Industries
- Tools & Libraries: Python, Scikit-learn, TensorFlow
- Introduction to Python and its Libraries (NumPy, Pandas, Matplotlib)
- Data Structures and Algorithms for Machine Learning
- Data Preprocessing: Handling Missing Values, Normalization, and Feature Engineering
- Exploratory Data Analysis (EDA) with Python
- Linear Regression: Simple and Multiple Linear Regression
- Logistic Regression for Classification
- Evaluation Metrics: Accuracy, Precision, Recall, F1-Score, ROC, and AUC
- Decision Trees: Classification and Regression Trees (CART)
- K-Nearest Neighbors (KNN)
- Support Vector Machines (SVM)
- Hands-on Projects: Predicting House Prices, Customer Churn Prediction
- Bagging and Boosting Techniques
- Random Forest
- AdaBoost
- Gradient Boosting (GBM, XGBoost, LightGBM)
- Model Tuning: Hyperparameter Tuning, Cross-Validation
- Stacking and Blending
- Hands-on Projects: Predicting Loan Defaults using Ensemble Models
- Introduction to Neural Networks
- Activation Functions, Forward and Backpropagation
- Deep Learning Frameworks: TensorFlow and Keras
- Convolutional Neural Networks (CNNs) for Image Processing
- Recurrent Neural Networks (RNNs) and LSTMs for Time Series Data
- Hands-on Projects: Image Classification, Sentiment Analysis
- Introduction to NLP: Text Preprocessing, Tokenization, Lemmatization
- Bag of Words (BoW), Term Frequency-Inverse Document Frequency (TF-IDF)
- Word Embeddings: Word2Vec, GloVe
- Text Classification with Machine Learning and Deep Learning Models
- Hands-on Projects: Spam Detection, Sentiment Analysis on Social Media
- Introduction to Reinforcement Learning
- Markov Decision Process (MDP)
- Q-Learning and Deep Q-Learning
- Applications of Reinforcement Learning
- Model Export and Deployment Techniques
- Using Flask or Django for Web App Integration
- Introduction to Cloud Platforms for Machine Learning: AWS, Google Cloud, Azure
- Deploying Models on the Cloud
- Hands-on Project: Deploying a Machine Learning Model
- Choose a real-world machine learning problem
- Apply the entire machine learning pipeline: Data collection, preprocessing, modeling, evaluation, and deployment
- Example Capstone Projects:
- Predictive Maintenance for Manufacturing
- Fraud Detection in Financial Transactions
- Recommender System for E-commerce
- Bias and Fairness in Machine Learning Models
- Interpretability of Machine Learning Models
- Ethical Concerns and Data Privacy Issues
- Ensuring Robustness and Security of Models
Industry Recognized Certification
MindForge Infotech
Machine Learning
Career Opportunities After Machine Learning Training
As a Machine Learning Engineer, you’ll be responsible for designing and implementing machine learning models that can learn from data and make predictions or decisions. This role involves working with algorithms, big data, and deployment pipelines. Machine Learning Engineers are highly sought after in industries like technology, finance, healthcare, and e-commerce.
₹ 3L – ₹ 12LPer AnnumHiring Companies
AI Engineers focus on creating intelligent systems and applications that mimic human learning and reasoning. They work on developing models for artificial intelligence (AI), including natural language processing (NLP), computer vision, and speech recognition. AI Engineers are instrumental in advancing technologies in sectors like robotics, autonomous vehicles, and smart assistants.
₹ 2L – ₹ 18.4LPer AnnumHiring Companies
With a background in machine learning, Data Analysts can leverage predictive models to enhance their analysis capabilities. They use machine learning algorithms to forecast trends, automate data processing, and provide deeper insights for businesses. This role is key in data-driven decision-making and is essential in industries like marketing, finance, and operations.
₹ 12.2L – ₹ 50LPer AnnumHiring Companies
Robotics Engineers use machine learning to enable robots to adapt and learn from their environment. This role is pivotal in industries such as manufacturing, healthcare, and autonomous systems. Machine learning allows robots to improve their performance over time, making them more efficient and responsive to changes.
₹ 12.2L – ₹ 50LPer AnnumHiring Companies
Specializing in deep learning, a branch of machine learning that uses neural networks, Deep Learning Specialists work on advanced projects such as image recognition, natural language processing, and autonomous systems. Their expertise is highly valued in sectors like healthcare, automotive, and artificial intelligence research.
₹ 12.2L – ₹ 50LPer AnnumHiring Companies
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MindForge Infotech is a registered trademark owned by EduCADD, pioneers in skill based learning for over 2 decades as a software training institute. MindForge is an idea derived with a vision to make quality Tech skill-oriented education available and affordable to every job aspiring youth of the nation. MindForge vision is implemented by relentlessly staying up with latest technology trends across the education value chain covering Grooming, Assessment, Industry ready skills and Soft skills to match requirements of industry today.
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- Assignment
- Mock Interviews
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- Free Online Workshops
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Learn from seasoned professionals with real-world experience in the IT industry.
Flexible Learning Options
Choose between online and in-person classes to suit your schedule and learning preferences.
Hands-On Training
Gain practical skills through hands-on projects and real-world case studies.
Certification Preparation
Prepare for industry-recognized certifications that enhance your employability and career prospects.
Job Placement Assistance
Benefit from dedicated career services, including job placement support and internship opportunities.
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Enjoy lifetime access to course materials, ensuring you can revisit and refresh your knowledge anytime.
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Best Machine Learning Training in India
Best Machine learning Training in India
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FAQ
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