Machine Learning & AI
12+
YEARS OF
EXPERIENCE
90k+
STUDENTS TRAINED
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100+
COMPANY
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- ABOUT
Your Dreams Deserve to be Realized, and we are here to Make It Happen
Welcome to Career Credentials, your trusted partner in career development and placement success. With a strong commitment to your professional growth, we empower individuals to unlock their full potential and secure their dream jobs with certainty. Join us at Career Credentials and unlock a world of opportunities. Ignite your potential, fuel your aspirations, and embark on a fulfilling career journey with the assurance of guaranteed job placements. Your dreams deserve to be realized, and we are here to make it happen.
- Academics
Course Curriculum
Week 1: Introduction to Machine Learning and AI
- Introduction to Machine Learning and AI
- Supervised, Unsupervised, and Reinforcement Learning
- Data preprocessing and feature engineering
- Evaluation metrics and model validation
- Introduction to Python libraries for Machine Learning (NumPy, Pandas, Scikit-learn)
Week 2: Supervised Learning Algorithms
- Linear Regression
- Logistic Regression
- Decision Trees and Random Forests
- Naive Bayes Classifier
- Support Vector Machines
Week 3: Unsupervised Learning Algorithms
- Clustering Algorithms (K-Means, DBSCAN, Hierarchical Clustering)
- Dimensionality Reduction (Principal Component Analysis, t-SNE)
- Association Rule Learning (Apriori, Eclat)
- Anomaly Detection
Week 4: Neural Networks and Deep Learning
- Introduction to Neural Networks
- Multi-layer Perceptron (MLP)
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Transfer Learning
Week 5: Natural Language Processing (NLP)
- Text Preprocessing
- Bag-of-Words and Word Embeddings
- Sentiment Analysis
- Named Entity Recognition
- Text Generation
Week 6: Computer Vision
- Image Processing and Feature Extraction
- Object Detection and Image Classification
- Image Segmentation
- Facial Recognition
- Image Generation and Style Transfer
Week 7: Reinforcement Learning
- Markov Decision Processes (MDPs)
- Q-Learning and Deep Q-Learning
- Policy Gradient Methods
- Applications of Reinforcement Learning
Week 8: Deploying ML Models and AI Ethics
- Model Deployment and Serving (REST APIs, Docker, Cloud Platforms)
- Interpretability and Explainability of ML Models
- Bias and Fairness in AI
- Privacy and Security Considerations
- Future Trends in Machine Learning and AI
- Technologies
Programming Languages & Tools
- Featured
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- Certifications
Our Certifications
IBM Certification
The Masters in Full Stack Developer Course offers three modules: Python for Web Developers, HTML-based Web Development, and Java Fundamentals. These modules teach essential job-ready skills like Python, databases, data analysis, and more. The course are streamlined to help you easily crack the IBM certification courses. You’ll gain hands-on experience on the IBM Cloud, working with real-world tools and datasets. By the end of the course, you’ll have a portfolio of Full Stack projects, setting you up for a successful career in Full Stack Development.
AWS Certifications
In the Full Stack Development Course offered by Career Credentials, you will be equipped with the necessary skills to assist organizations in identifying and nurturing talent capable of implementing cloud initiatives. The course emphasizes the importance of becoming an AWS Certified Cloud Practitioner, as it demonstrates proficiency in cloud technologies and establishes a solid foundation of AWS knowledge. By obtaining this certification, you validate your expertise in the cloud domain and enhance your career prospects in Full Stack Development.
- Testimonials
Trusted by 90,000+ Student
Career Credentials provided a strong foundation for my full stack development career. The instructors were patient, and their industry connections led to multiple job offers before course completion.
Best career decision! Career Credentials' curriculum was comprehensive and well-paced. The instructors were experts and offered outstanding post-course support. I secured multiple job offers within a month!
- FAQ's
Frequently Asked Questions
What is Machine Learning and AI, and why are they important?
Machine Learning is a subset of Artificial Intelligence (AI) that focuses on building algorithms and models that enable computers to learn from data and make predictions or decisions. AI, on the other hand, encompasses broader concepts and techniques that simulate human intelligence. Machine Learning and AI are important because they can automate processes, make accurate predictions, and provide valuable insights across various industries.
What will I learn in the Machine Learning & AI course?
In this course, you will learn fundamental concepts of Machine Learning and AI, including supervised and unsupervised learning algorithms, neural networks, deep learning, natural language processing (NLP), and computer vision. You will also gain hands-on experience with popular programming languages like Python and tools like TensorFlow and scikit-learn.
Are there any prerequisites for the Machine Learning & AI course?
Prior knowledge of programming, statistics, and linear algebra is recommended for this course. Familiarity with Python programming language will be beneficial, as most of the hands-on exercises and projects will be implemented using Python libraries.
How long does the Machine Learning & AI course take?
The course duration is typically 8 to 12 weeks, depending on the curriculum’s depth and the pace of learning. It is designed to provide a comprehensive understanding of Machine Learning and AI concepts and techniques within a reasonable timeframe.
Will I receive a certificate upon completion?
Yes, upon successfully completing the course, you will receive a certificate that validates your skills and knowledge in Machine Learning and AI. This certificate can enhance your resume and demonstrate your proficiency in developing and implementing Machine Learning models.
How can Machine Learning & AI skills benefit my career?
Machine Learning and AI skills are highly sought after in various industries, including finance, healthcare, e-commerce, and technology. By acquiring these skills, you can pursue career opportunities as a Machine Learning Engineer, Data Scientist, AI Specialist, or AI Consultant. These roles often offer competitive salaries and provide opportunities for innovation and solving complex problems.
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