AI and ML Courses in Hyderabad
Empower Your Future with Careerpedia's AI and ML Courses, Join the AI and ML course in Hyderabad, and become an expert in Machine Learning & Artificial Intelligence.
continuous learning
- Supervised Learning Model - Regression
- Simple linear regression in python
- Multiple Linear Regression
- Multiple Linear Regression in Python
- Industry Relevance of Linear Regression
- Supervised Learning Model - Classification
- Univariate Logistic Regression
- Multivariate Logistic Regression - Model Building
- Multivariate Logistic Regression - Model Evaluation
- Logistic Regression - Industry Applications
- Unsupervised Learning: Clustering
- Introduction to Clustering
- K Means Clustering
- Executing K Means in Python
- Hierarchical Clustering
- Tree Models
- Introduction to Decision Trees
- Algorithms for Decision Tree Construction
- Hyperparameter Tuning in Decision Trees
- Ensembles and Random Forests
- Time Series Forecasting - I (BA)
- Introduction to Time Series
- Smoothing Techniques
- Practice Questions
- Common Interview Questions
- Time Series Forecasting - II (BA)
- Introduction to AR Models
- Building AR Models
- Practice Questions
- Model Selection
- Principles of Model Selection
- Model Building and Evaluation
- Introduction to NLP
- What is NLP?
- History and evolution of NLP
- Applications of NLP
- Challenges in NLP
- Overview of NLP pipeline
- Corpus and Corpus Linguistics
- NLTK Toolkit
- Introduction to the NLTK toolkit
- Preprocessing text data with NLTK
- Basic NLP tasks using NLTK (e.g., Part-of-Speech Tagging, Named Entity Recognition)
- Stemming and Lemmatization
- WordNet in NLTK
- Chunking and Chinking
- Sentiment Analysis with NLTK
- Tokenization and Topic Modeling
- Tokenization in NLP
- Bag-of-Words representation
- Topic Modeling with LDA
- Latent Semantic Analysis
- Word Embeddings
- Sentiment Analysis Project:
- Introduction to Sentiment Analysis
- Sentiment Analysis using supervised and unsupervised methods
- Building a Sentiment Analysis model with Python
- Evaluating Sentiment Analysis models
- Power AI vs Deep Learning vs ML BI
- Introduction to Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL)
- Applications of AI, ML, and DL
- Differences between AI, ML and DL
- The Concept of Neural Networks
- Introduction to Neural Networks
- Types of Neural Networks
- Layers in Neural Networks
- Activation Functions
- Neural Networks - Feed-forward, Convolutional, Recurrent
- Feed-forward Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Applications of Neural Networks
- Deep Learning Project
- Building a Deep Learning model with Python
- Image Classification with Convolutional Neural Networks
- Natural Language Processing with Recurrent Neural Networks
- Hyperparameter Tuning in Deep Learning
- Generative AI
- 1. Generative AI basics.
- 2. GANs: Generator vs. Discriminator.
- 3. VAEs: Encoding and Decoding.
- 4. Text Generation with RNNs and LSTMs.
- 5. Image Generation Techniques.
- 6. Music Generation with NNs.
- 7. Conditional GANs.
- 8. Style Transfer.
- 9. Evaluation Metrics.
- 10. Real-world Applications & Prompt Engineering.
Process of Careerpedia
From enrolment to placement, our streamlined process ensures a smooth journey toward your academic and career goals
Demo Section
Students will be given a brief outlook of their respective courses. In this particular session students will get to know what kind of software's they are going to use, How training sessions are going to be conducted, How they are going to evaluate themselves going further.
- Students will be given a brief outlook of their respective courses.
- In this particular session students will get to know what kind of software they are going to use.
- How training sessions are going to be conducted.
- How they are going to evaluate themselves in future.
Onboarding
- Orienting new students to the organization. It encompasses all activities and procedures that help new students become more productive.
- Here students will be given access to the necessary tools, software's, resources required for the training.
- Students will engage with their respective mentors.
Orienting new students to the organization. It encompasses all activities and procedures that help new students become more productive Here students will be given access to the necessary tools, software's, resources required for the training, Students will engage with their respective mentors.
Learning
- Mentors will observe the students during class activities, discussions, understanding and active participation in the tasks.
- Mentors will help in achieving academic success and also share continuous feedback.
- Mentors also provide guidance, support and advice to less experienced students.
Mentors will observe the students during class activities, discussions, understanding and active participation in the tasks. Mentors will help in achieving academic success also shares continuous feedback.
Test Assignment
- The test will be conducted weekly once on their respective courses.
- It can help students to identify their strengths and weaknesses so they can focus on areas that need improvement.
- Successfully completing tasks and achieving good grades will boost students' confidence.
The test will be conducted weekly once on their respective courses, it can help students to identify their strengths and weaknesses so they can focus on areas that need improvement.
Communication Club
- Communication Club will be taken daily for the students.
- Students will receive their respective scores and suggestions.
- It will help students for active participation in the real time interviews.
Communication Club will be taken daily for the students. Students will receive their respective score and suggestions.
Mock Interviews
- Mock Interviews will be taken every Friday.
- It helps you to develop interview strategies, enhance your communication skills, and ease the nerves that many experience before an actual job interview.
- Mock interviews may be conducted by professionals or recruiters in the field.
Mock Interviews will be taken on every Friday. It helps you to develop interview strategies, enhance your communication skills, and ease the nerves that many experiences before an actual job interview.
Profile Building
- Portfolio, Resume & LinkedIn profile building
After completing the 70% of course. Mentors will assist the students on profile building like, Portfolio, Resume and LinkedIn profile.
Job Portal
- After completion of profile building, the job portal access will be given to students.
- It simplifies the job search process.
- The job assistance will be up-to one year.
After completion of profile building, the job portal access will be give to students. It simplify the job search process, The job assistance will be up to one year.
Certification
Careerpedia certifications offer global recognition and access.
Enroll for collaboration and networking opportunities at Careerpedia
Connect with professionals, instructors, and peers at Careerpedia.
What Students Says about Careerpedia
Testimonials
Join the Careerpedia community and dive into the engaging testimonials from our students, as they offer valuable insights and experiences.
Vamshi
Full stack Developer
Jadhav Pranay Singh
UIUX Developer
B Venkaiahnaidu
Frontend Developer
Abhishek Maddala
UIUX Developer
Yugender Senkepally
UIUX Developer
Kalyan
UIUX Designer
Devendar Reddy
UIUX Designer
Vijaya Sree
Front end Developer
Overview of AI and ML course in Hyderabad
Careerpedia's AI and ML course in Hyderabad is designed to equip students with the knowledge and skills necessary to excel in the rapidly growing fields of artificial intelligence and machine learning. This comprehensive program covers a wide array of topics, from foundational concepts to advanced techniques, ensuring a well-rounded understanding of AI and ML.
Artificial Intelligence (AI) and Machine Learning (ML) are cutting-edge technologies that enable machines to perform tasks that typically require human intelligence. AI focuses on creating smart machines that can learn, solve problems, and understand languages. There are two types of AI: narrow AI, which is designed for specific tasks, and general AI, which aims to perform any intellectual task that a human can do.
Machine Learning (ML) is a subset of AI where machines learn from data without explicit programming. ML algorithms identify patterns and make predictions based on data. They continuously improve as they are exposed to more data. ML applications include recommendation systems, sales forecasting, and medical diagnostics.
- Supervised Learning -Regression
- Supervised Learning - Classification
- Unsupervised Learning - Clustering
- Tree Models
- Time Series Forecasting
- Model Selection
- Natural Language Processing (NLP)
- NLTK Toolkit
- Tokenization and Topic Modeling
- Sentiment Analysis Project
- Neural Networks
- Deep Learning Project
- Generative AI
Here are some benefits of Careerpedia's AI and ML Course:
- Skill Acquisition: Gain comprehensive knowledge and practical skills in AI and ML, which are in high demand in the tech industry.
- Career Advancement: Enhance your job prospects and open up diverse career opportunities by completing Careerpedia's AI and ML course in Hyderabad.
- Hands-on Experience: Work on real-world projects to build a professional portfolio and gain practical experience in AI and ML course.
- Expert Instruction: Learn from experienced instructors who provide valuable insights and industry-relevant knowledge in AI and ML course.
- Flexible Learning Options: Careerpedia’s AI and ML course in Hyderabad offers both offline classes and online courses accessible from anywhere.
- Industry Readiness: Be prepared for the demands and challenges of the AI and ML industry with a comprehensive and practical curriculum.
- Cutting-edge Tools and Techniques: Stay updated with the latest tools, technologies, and methodologies in AI and ML by enrolling in Careerpedia's course.