Natural Language Processing
Internship 2024
Career-Based Complete Artificial Intelligence Internship Program. Get Insights into: Python , Machine & Deep Learning concepts with Project Implementation and Assignments.
1/ 2 Months
Online
8+ Live Projects
Dual Certification
Ultimate Step towards your Career Goals: Expert in AI Technologies
Get ahead with the FutureTech Industrial Internship Program: gain hands-on experience, connect with industry leaders, and develop cutting-edge skills. Earn a stipend, receive expert mentorship, and obtain a certificate to boost your career prospects. Transform your future with practical, real-world learning today
Internship Benifits
Mentorship
Receive guidance and insights from industry experts.
Hands-on Experience
Gain practical skills in a real-world cutting-edge projects.
Networking
Connect with professionals and peers in your field.
Skill Development
Enhance your technical and soft skills.
Career Advancement
Boost your resume with valuable experience.
Certificate
Get a certification to showcase your achievements.
AI Internship Overview
Key Notes:
Comprehensive Learning: Covers both foundational and advanced concepts in NLP and machine learning.
Hands-On Projects: Practical projects to apply learned techniques.
Advanced Techniques: Detailed exploration of RNN, LSTM, and transformers.
Tools and Frameworks: Mastering tools like TensorFlow, PyTorch, and Hugging Face.
This course provides a deep dive into NLP, machine learning, and deep learning, equipping you with the skills to innovate and excel in these dynamic fields. Ready to elevate your expertise? Let’s get started!
Introduction to NLP and Machine Learning
Overview: Understand the basics and significance of Natural Language Processing (NLP) and machine learning.
Regex: Learn regular expressions for text pattern matching.
Pandas for NLP: Utilize Pandas for handling and analyzing text data.
Text Preprocessing Techniques
Tokenization, Stemming, Lemmatization, Stop Words: Fundamental steps to prepare text for analysis.
Bag of Words, TFIDF, Ngrams: Methods to convert text into numerical formats for machine learning.
Practical Applications
Sentiment Classification on Amazon Reviews: Analyzing customer sentiment using machine learning.
Deep Learning Basics
Introduction to Deep Learning: Basic concepts of deep learning.
TensorFlow Basics: Setting up and using TensorFlow for deep learning tasks.
Advanced Preprocessing
Word2Vec, Average Word2Vec: Techniques for word representation.
Implementation: Practical application of advanced preprocessing methods.
Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)
RNN and LSTM Architecture Walkthrough: Understanding the structure and functionality of RNNs and LSTMs.
Next Word Prediction Using LSTM: Building predictive text models.
Generating Poetic Text Using LSTM: Creative applications of LSTM for generating poetry.
Fake News Classifier Using Bidirectional LSTM: Detecting misinformation using Bidirectional LSTMs.
Sequence to Sequence (Seq2Seq) Models
Text Summarization Using LSTM Encoder-Decoder Architecture: Implementing Seq2Seq models for summarizing text.
Large Language Models (LLM)
Introduction to LLM and Transformer Architecture: Basics of large language models and transformers.
Hugging Face: Fine-tuning pretrained models on custom datasets.
LangChain Applications:
Chat with Books and PDF Files Using Llama 2 and Pinecone: Advanced NLP applications for document interactions.
Blog Generation LLM App Using Llama 2: Creating a blog generation application.
SQL Query LLM Using Google Gemini: Using LLM for SQL queries.
YouTube Video Transcribe Summarizer LLM App with Google Gemini: Summarizing YouTube videos.
Looking for in-depth Syllabus Information? Explore your endless possibilities in AI with our Brochure!
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Project Submission: Example Output Screenshots from Our Clients
Take a look at these sample outputs crafted by our clients. These screenshots showcase the impressive results achieved through our courses and projects. Be inspired by their work and visualize what you can create!
Dual Certification: Internship Completion & Participation
Earn prestigious Dual Certification upon successful completion of our internship program. This recognition validates both your participation and the skills you have honed during the internship, providing a competitive edge in your professional journey. Show off your expertise with pride!
How does this Internship Program Work?
Step 1 Enroll in the Program
✅ Get a Mentor Assigned
✅Presentations & Practice Codes
✅ Learn at your Flexible Time
✅ Apprehend the concepts
Step 2 Project Development
✅ Implement Skills Learn
✅ Develop Projects with assistance
✅ Get Codes for Reference
✅ Visualise the Concepts
Step 3 Certification
✅ Get Certified
✅ Certificate of Internship
✅ Project Completion Certificate
✅ Share on social media
✅ Get Job Notifications
Internship Letter (LoR)
Internship Report
Flexible Schedules
1 Month
₹1999/-
1 Month
- Internship Acceptance Letter
- 90 Days from the date of payment
- 4 LIVE interactive Mastermind Sessions
- 4+ Capstone Projects & Codes
- Full Roadmap
- Internship Report
- 1 Month Internship Certificate
₹3299/-
2 Month
- Internship Acceptance Letter
- 180 Days from the date of payment
- 4 LIVE interactive Mastermind Sessions
- 12+ Capstone Projects & Codes
- Full Roadmap
- Internship Report
- Participation Certificate
- 2 Month Internship Certificate
Our Alumni Employers
Curious where our graduates make their mark? Our students go on to excel in leading tech companies, innovative startups, and prestigious research institutions. Their advanced skills and hands-on experience make them highly sought-after professionals in the industry.
FAQ
What kind of projects will I work on?
Projects range from basic tasks like building a recommendation system or salary prediction model to advanced projects like image classification, face recognition, and NLP applications.
What is AI?
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and solve problems.
What is Python and why is it important?
Python is a popular programming language known for its simplicity and readability, making it perfect for beginners and widely used in AI and machine learning.
What are machine learning and deep learning?
Machine learning is a subset of AI focused on building algorithms that enable computers to learn from and make predictions based on data. Deep learning is a further subset that uses neural networks with many layers to analyze various factors of data.
What are the basic steps to start learning AI?
Begin with understanding Python programming, then move on to learning key libraries like NumPy, Pandas, and Scikit-learn, followed by studying machine learning and deep learning concepts.
What resources can I use to practice my skills?
Utilize online tutorials, coding platforms like GitHub, and participate in competitions on sites like Kaggle to enhance your learning.
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