Software Training Institute in Chennai with 100% Placements – SLA Institute

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Artificial Intelligence And Data Science Syllabus

(1987)
Live Online & Classroom Training
EMI
0% Interest

Boost your career with our Artificial Intelligence Training in OMR at SLA Institute! This practical course covers key AI topics like neural networks, deep learning, and natural language processing, all taught by experienced instructors. You’ll gain hands-on experience through real-world projects and problem-solving. Plus, with the Artificial Intelligence Course in OMR with 100% Placement Support, we’ll help you find a job in the exciting field of AI. Sign up at SLA Institute today and take the first step towards a successful career in artificial intelligence!

At SLA Institute, we guarantee placement in a high-paying Developer job with the support of our experienced placement officers. Our Artificial Intelligence Course in OMR Syllabus covers all essential topics, providing you with a comprehensive understanding of Artificial Intelligence development.

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Upcoming Batches

Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
January 2025
Week days
(Mon-Fri)
Online/Offline

2 Hours Real Time Interactive Technical Training 

1 Hour Aptitude 

1 Hour Communication & Soft Skills

(Suitable for Fresh Jobseekers / Non IT to IT transition)

Course Fee
January 2025
Week ends
(Sat-Sun)
Online/Offline

4 Hours Real Time Interactive Technical Training

(Suitable for working IT Professionals)

Course Fee

Save up to 20% in your Course Fee on our Job Seeker Course Series

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Placement

100% Assistance

Learning

Job-Centered Approach

Timings

Convenient Hrs

Mode

Online & Classroom

Certification

Industry-Accredited

This Course Includes

  • FREE Demo Class
  • 0% EMI Loan Facilities
  • FREE Softskill & Placement Training
  • Tie up with more than 500+ MNCs & Medium Level Companies
  • 100% FREE Placement Assistance
  • Course Completion Certificate
  • Training with Real Time Projects
  • Industry-Based Coaching By MNC IT Professionals
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Expected Criteria for Assured Placement

The following criteria help the placement team guide the candidates to get placed immediately after the course completion through SLA Institute.

  • 80% of coursework completion helps us arrange interviews in required companies.
  • 2 or 3 projects to be done for the selected course to ace the technical round effectively.
  • Ensure attending the placement training right from the first day of the selected course.
  • Practice well with resume building, soft skill, aptitude skill, and profile strengthening.
  • Utilize the internship training program at SLA for the complete technical skills.
  • Collect the course completion certificate and update the copy to the placement team.
  • Ensure your performance indicator meets the expectation of top companies.
  • Always be ready with the updated resume that includes project details done at SLA.
  • Enjoy unlimited interview arrangements along with internal mock interviews.
Have Queries? Ask our Experts

+91 89256 88858

SLA's Distinctive Placement Approach

1

Tech Courses

2

Expert Mentors

3

Assignments & Projects

4

Grooming sessions

5

Mock Interviews

6

Placements

Achieve Your Goals With SLA

SLA builds your future with comprehensive coursework and unparalleled placement support.
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Artificial Intelligence And Data Science Syllabus Course Syllabus

Download Syllabus

Join our Artificial Intelligence Training in OMR to become a skilled professional in AI development and implementation. Start with fundamental programming skills and advance to sophisticated AI frameworks and tools. At SLA Institute, you’ll get practical experience with real-world projects, receive expert guidance, and enjoy dedicated job placement support. Enroll today to kickstart your career in Artificial Intelligence and open doors to exciting opportunities in the tech world.

Module 1: Introduction to AI and Data Science
  • Overview of Artificial Intelligence (AI) and Data Science
  • History and evolution of AI
  • Applications of AI in various industries
  • Introduction to Data Science and its importance
  • Tools and technologies in AI and Data Science
Module 2: Programming for AI and Data Science
  • Python programming basics for AI and Data Science
  • Libraries: NumPy, Pandas, Matplotlib, Seaborn
  • Data structures and algorithms
  • Introduction to Jupyter Notebook
Module 3: Data Preprocessing and Exploration
  • Data cleaning and handling missing data
  • Feature selection and extraction
  • Exploratory Data Analysis (EDA)
  • Data visualization techniques using Python
  • Working with large datasets
Module 4: Machine Learning Fundamentals
  • Introduction to Machine Learning (ML)
  • Supervised learning: Linear regression, Logistic regression, Decision trees
  • Unsupervised learning: K-means clustering, Hierarchical clustering
  • Evaluation metrics: Accuracy, Precision, Recall, F1-score
  • Cross-validation and model selection
Module 5: Advanced Machine Learning Algorithms
  • Support Vector Machines (SVM)
  • Random Forests and Ensemble Methods
  • K-Nearest Neighbors (KNN)
  • Naive Bayes Classifier
  • Hyperparameter tuning
Module 6: Deep Learning and Neural Networks
  • Introduction to Deep Learning
  • Neural Networks and architecture
  • Backpropagation and Gradient Descent
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Introduction to TensorFlow and Keras
Module 7: Natural Language Processing (NLP)
  • Introduction to NLP and text mining
  • Text preprocessing: Tokenization, Lemmatization, and Stopwords removal
  • Sentiment analysis and text classification
  • Word embeddings: Word2Vec, GloVe
  • Introduction to NLTK and spaCy
Module 8: Data Science and AI in Business
  • AI in business applications: Marketing, Finance, Healthcare
  • Predictive analytics and recommendation systems
  • Time series analysis and forecasting
  • Case studies of AI and Data Science in real-world scenarios
Module 9: Big Data and AI
  • Introduction to Big Data technologies
  • Hadoop, Spark, and distributed computing
  • Data processing and management with Big Data tools
  • Scaling AI models with Big Data
Module 10: AI and Data Science Ethics and Future Trends
  • Ethical considerations in AI
  • Bias in AI models and fairness
  • AI safety and regulations
  • Future trends in AI and Data Science
Module 11: Capstone Project
  • Hands-on project involving real-world datasets
  • End-to-end AI and Data Science solution implementation
  • Model building, evaluation, and deployment
  • Presenting findings and insights
Module 12: Career Preparation and Job Readiness
  • Resume building and interview preparation
  • Soft skills and communication for Data Scientists and AI Engineers
  • Placement assistance and job opportunities in AI and Data Science

Project Practices on Artificial Intelligence And Data Science Syllabus Training

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The Placement Process at SLA Institute

  • To Foster the employability skills among the students
  • Making the students future-ready
  • Career counseling as and when needed
  • Provide equal chances to all students
  • Providing placement help even after completing the course
On Average Students Rated The Artificial Intelligence And Data Science Syllabus Course 4.70/5.0
(1987)
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