Artificial Intelligence Training In Bangalore 100% Job Guarantee

  • Provided by a Certified Artificial Intelligence Expert with Over ten years of experience.
  • 320+ Employing Clients and Over 11402 Students Trained.
  • The Greatest Methods for Nominal Cost Trending Concepts.
  • Learn Top Tips for Novice to Expert Level Courses.
  • Trendy Projects and Advanced Research Resources are available.
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Curriculum in Artificial Intelligence

Foundation of AI & ML
  • Introduction to Data Science, AI&ML
  • R Essentials
  • Statistical Analysis
    • Python for Artificial Intelligence
  • Python Essentials
  • Python Environment Setup
  • Python Data Types
  • Python Looping and Control Statements
  • Object-Oriented Programming Concepts
  • Database Connection
    • Python Libraries for Artificial Intelligence
  • Numpy
  • Scipy
  • Pandas
  • MatPlot
    • Data Management
  • Data Acquisition
  • Data Pre-processing and Preparation
  • Data Transformation and Quality
  • Handling Text Data
  • Big Data Fundamentals
  • Big Data Frameworks(Spark, Hadoop, NoSQL)
    • SAS-Data Analytics
  • SAS Introduction
  • SAS Functions
  • SAS Operators
  • SAS Procedures
  • SAS Graphs
  • SAS Macros
  • SAS Format
    • Statistical Decision Making
  • Data Visualisation
  • Sampling and Estimation
  • Inferential Statistics
    • Predictive Analytics
  • Linear Regression
  • Multiple Linear Regression
  • Non-Linear Regression
  • Forecasting Models
    • Machine Learning
  • ML Foundations
  • Clustering
  • Classification(Naive Bayes Classifier, K-Nearest Neighbors)
  • Association Rule Mining
    • Artificial Intelligence
  • Foundations of AI
  • Convolution Neural Networks
  • Recurrent Neural Networks
    • Deep Learning with Keras and TensorFlow
  • Deep Learning Libraries
  • Keras API
  • TensorFlow
  • Deep Learning Algorithms
    • Advanced Deep Learning and Computer Vision
  • Distributed and Parallel Computing
  • Deploying Deep Learning Models
  • Reinforcement Learning
  • Generating Images with Neural Style
  • Object Detection through Convolutional Neural Networks
    • Cloud Computing and AWS
  • Introduction to Cloud Computing and AWS
  • Storage Volumes and Elastic Compute
  • Virtual Private Cloud
  • Simple Storage Services
  • AWS Lambda and Amazon Machine Learning
    • Tableau 10
  • Introduction to Data Visualisation
  • Tableau Architecture
  • Working with Data Blending
  • Creation of Sets
  • Calculations, Expression, and Parameters
  • Dashboards, Stories, and Filters
  • Tableau Prep

    • Curriculum in Artificial Intelligence

    Artificial Intelligence Is Preferred by Over 35% of Developers. Artificial Intelligence is the most widely used and in-demand programming language in the IT industry.

    • Introduction to Data Science, AI&ML
    • R Essentials
    • Statistical Analysis
    • Python Essentials
    • Python Environment Setup
    • Python Data Types
    • Python Looping and Control Statements
    • Object-Oriented Programming Concepts
    • Database Connection
    • Numpy
    • Scipy
    • Pandas
    • MatPlot
    • Data Acquisition
    • Data Pre-processing and Preparation
    • Data Transformation and Quality
    • Handling Text Data
    • Big Data Fundamentals
    • Big Data Frameworks(Spark, Hadoop, NoSQL)
    • SAS Introduction
    • SAS Functions
    • SAS Operators
    • SAS Procedures
    • SAS Graphs
    • SAS Macros
    • SAS Format
    • Data Visualisation
    • Sampling and Estimation
    • Inferential Statistics
    • Linear Regression
    • Multiple Linear Regression
    • Non-Linear Regression
    • Forecasting Models
    • ML Foundations
    • Clustering
    • Classification(Naive Bayes Classifier, K-Nearest Neighbors)
    • Association Rule Mining
    • Foundations of AI
    • Convolution Neural Networks
    • Recurrent Neural Networks
    • Deep Learning Libraries
    • Keras API
    • TensorFlow
    • Deep Learning Algorithms
    • Distributed and Parallel Computing
    • Deploying Deep Learning Models
    • Reinforcement Learning
    • Generating Images with Neural Style
    • Object Detection through Convolutional Neural Networks
    • Introduction to Cloud Computing and AWS
    • Storage Volumes and Elastic Compute
    • Virtual Private Cloud
    • Simple Storage Services
    • AWS Lambda and Amazon Machine Learning
    • Introduction to Data Visualisation
    • Tableau Architecture
    • Working with Data Blending
    • Creation of Sets
    • Calculations, Expression, and Parameters
    • Dashboards, Stories, and Filters
    • Tableau Prep

    Artificial Intelligence Training Projects

    Develop Your Artificial Intelligence Skills With Useful and Interesting Projects.

     

    Simple Chatbot

    Build a basic conversational agent using rule-based or retrieval-based techniques.

     

    Handwritten Digit Recognition

    Develop a model to classify handwritten digits using machine learning algorithms like logistic regression or k-nearest neighbors.

     

    Image Classification

    Create a classifier to distinguish between different categories of images, such as cats vs. dogs.

     

    Object Detection

    Develop a model to detect and localize objects within images using techniques like Faster R-CNN or YOLO.

     

    Facial Recognition

    Build a system capable of recognizing faces in images or videos using deep learning models like CNNs or Siamese networks.

     

    Stock Price Prediction

    Develop a model to predict the future prices of stocks based on historical market data.

     

    Language Translation

    Create a neural machine translation system capable of translating text between multiple languages.

     

    Video Action Recognition

    Develop a model to recognize and classify human actions in videos, such as walking, running, or sitting.

     

    Generative Adversarial Networks (GANs)

    Implement GANs to generate realistic images or videos, such as faces or landscapes.

    Best Industry Tools Covered

    Key Highlights

    Practical Training

    Global Certifications

    Flexible Timing

    Trainer Support

    Study Material

    Placement Support

    Mock Interviews

    Resume Building

    Our Instructor

    Get advice from specialists who have certifications and are currently working.

    Instructor
    Pooja

    Experience : 3 Years

    Pooja is a highly skilled AI and machine learning engineer with expertise in building and deploying advanced models for various applications.

    Specialized in : Python Programming, Machine Learning Algorithms, Natural Language Processing, Deep Learning, TensorFlow, and PyTorch.

    Instructor
    Ankit

    Experience : 4 Years

    Ankit is a seasoned big data architect and consultant, proficient in designing and implementing scalable data solutions for enterprises.

    Specialized in : Big Data Analytics, Hadoop, Spark, Scala, Apache Kafka, Apache Hive, and Apache HBase.

    Instructor
    Neha

    Experience : 4 Years

    Neha is an expert data engineer with hands-on experience in building robust data pipelines and optimizing data workflows for efficiency and reliability.

    Specialized on : Data Engineering, ETL (Extract, Transform, Load) Processes, Data Warehousing, Apache Airflow, Apache Beam, and Google Cloud Platform (GCP).

    Artificial Intelligence Training Overview

    Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, typically through computer systems. It encompasses a broad spectrum of technologies and methodologies aimed at enabling machines to perform tasks that traditionally require human intelligence, such as learning, reasoning, problem-solving, perception, and language understanding. At its core, AI seeks to replicate cognitive abilities and decision-making processes exhibited by humans, thereby enhancing efficiency, accuracy, and automation across various domains and industries. From self-driving cars and virtual assistants to medical diagnosis and financial forecasting, AI applications are transforming the way we live, work, and interact with technology. Through the use of algorithms, data analysis, machine learning, and other advanced techniques, AI systems can perceive their environment, learn from experience, and adapt to new situations, leading to unprecedented advancements in innovation and productivity.

    Additional Information

    Artificial Intelligence Programmer’s Potential Career Paths

    • Machine learning engineers focus on designing, implementing, and deploying machine learning models and algorithms to solve specific problems, such as image recognition, natural language processing, or recommendation systems.
    • Data scientists utilize AI and machine learning techniques to analyze large datasets, extract insights, and make data-driven decisions. They often work on predictive modeling, data visualization, and statistical analysis projects.
    • AI research scientists conduct theoretical and experimental research to advance the field of artificial intelligence. They may work on developing new algorithms, improving existing techniques, or exploring novel applications of AI.
    • Software developers specializing in AI focus on integrating AI capabilities into software applications and systems. They may work on developing AI-powered features, APIs, or libraries that enable AI functionality.

    Reasons to Consider Enrolling in Artificial Intelligence Training

    • AI is rapidly transforming industries across the globe, leading to a surge in demand for professionals with AI expertise. By acquiring AI skills through training, individuals can position themselves for lucrative career opportunities in fields such as data science, machine learning, robotics, and natural language processing.
    • AI training can open doors to new career paths and opportunities for advancement. With AI skills in high demand, individuals who possess expertise in areas such as machine learning, deep learning, and AI programming are highly sought after by employers seeking to drive innovation and remain competitive in today's digital economy.
    • AI training equips individuals with the knowledge and tools to develop innovative solutions to complex problems. By mastering AI algorithms, techniques, and methodologies, individuals can tackle real-world challenges in areas such as healthcare, finance, transportation, and manufacturing, driving progress and innovation in their respective fields.
    • AI training provides a valuable opportunity for personal and professional growth. Whether you are a seasoned professional looking to expand your skill set or a student exploring new areas of interest, AI training can help you develop critical thinking, problem-solving, and analytical skills that are essential in today's technology-driven world.

    Techniques and Trends in Artificial Intelligence Development

    Artificial intelligence (AI) development is characterized by a wide range of techniques and trends that are constantly evolving. Some of the prominent techniques and trends in AI development include:

    • ML is a subset of AI that focuses on developing algorithms and models that enable computers to learn from data and make predictions or decisions without being explicitly programmed. Supervised learning, unsupervised learning, and reinforcement learning are common ML techniques used in AI development.
    • Deep learning is a subset of ML that uses artificial neural networks with multiple layers to learn complex patterns and representations from large amounts of data. Deep learning techniques, such as convolutional neural networks (CNNs) for image recognition and recurrent neural networks (RNNs) for sequential data processing, have achieved remarkable success in various AI applications.
    • Techniques such as word embeddings, recurrent neural networks (RNNs), and transformer models like BERT have significantly advanced NLP tasks such as language translation, sentiment analysis, text summarization, and question answering.
    • Techniques such as object detection, image classification, semantic segmentation, and image generation using deep learning models have led to advancements in areas such as autonomous vehicles, medical imaging, facial recognition, and surveillance systems.

    The Most Recent Artificial Intelligence Tools

    • OpenAI's Generative Pre-trained Transformer 3 (GPT-3) is one of the most powerful natural language processing models to date. It can generate human-like text based on prompts, perform language translation, answer questions, and more.
    • Hugging Face provides a library and platform for developers to access state-of-the-art natural language processing models, including BERT, GPT-2, and various transformer-based models, for tasks such as text classification, summarization, and conversational AI.
    • PyTorch Lightning is a lightweight wrapper for PyTorch that simplifies the training process of deep learning models. It provides a high-level interface for organizing code, handling distributed training, and logging experiment metrics.
    • TensorFlow Extended is an end-to-end platform for deploying production-ready machine learning pipelines. It includes components for data validation, transformation, model training, and serving, enabling seamless integration of ML models into production systems.
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    Artificial Intelligence Training Objectives

  • Machine Learning Engineer
  • Data Scientist
  • AI Researcher
  • Natural Language Processing (NLP) Engineer
  • Computer Vision Engineer
  • AI Software Developer
  • AI Consultant
  • AI Product Manager
  • Robotics Engineer
  • Business Intelligence Analyst

    • Yes, many certification exams for artificial intelligence can be taken online. Online proctoring services allow candidates to take exams remotely from their own computers while ensuring the integrity and security of the testing process. Candidates typically need to register for the exam through the certification provider's website, schedule a suitable exam date and time, and follow the specified instructions for online proctoring.

    The requirements to become certified in artificial intelligence can vary depending on the certification program and provider. However, common prerequisites may include a foundational understanding of mathematics (calculus, linear algebra, probability), proficiency in programming languages like Python, familiarity with AI concepts and techniques, and completion of relevant coursework or training. Candidates may also need to pass a certification exam to demonstrate their knowledge and skills in artificial intelligence.

  • Understanding machine learning methods and methodologies.
  • Capability to handle big datasets and do data preparation.
  • Understanding of deep learning frameworks such as TensorFlow or PyTorch.
  • Familiar with AI development tools and frameworks.
  • Problem-solving and critical thinking abilities.
  • Ability to evaluate and convey AI model results.
  • Google Cloud (e.g., Google Cloud AI Platform Professional Certificate)
  • IBM (e.g., IBM AI Engineering Professional Certificate)
  • Microsoft (e.g., Microsoft Certified: Azure AI Fundamentals)
  • Amazon Web Services (e.g., AWS Certified Machine Learning - Specialty)
  • These certifications validate your expertise in artificial intelligence and are recognized by employers worldwide.
  • Enhancing your credentials and credibility as an AI professional
  • Increasing your job prospects and opportunities for career advancement
  • Demonstrating your expertise and proficiency in AI technologies to employers
  • Keeping you updated with the latest trends and advancements in the field
  • Opening up new career paths and specialties within the field of artificial intelligence
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    Industry Statistics

    Jobs / Month

    248

    Avg. Salary

    ₹ 12,55,200

    Job Roles

    AI/ML Engineer

    Data Scientist

    Robotics Engineer

    AI Consultant

    Artificial Intelligence Certification

    Certificate
    GET A SAMPLE CERTIFICATE
  • Validation of expertise and proficiency in AI technologies.
  • Increased credibility and marketability in the job market.
  • Access to exclusive job opportunities and higher salary prospects.
  • Structured learning and skill development in specialized areas of AI.
  • Networking opportunities with professionals in the AI field.
  • Recognition by employers and industry stakeholders.

    • Yes, there are several artificial intelligence certifications available, offered by various organizations, institutions, and technology companies. These certifications may focus on different aspects of AI, such as machine learning, deep learning, natural language processing, computer vision, robotics, and AI ethics. Some popular AI certification providers include Google, IBM, Microsoft, Amazon Web Services (AWS), NVIDIA, Coursera, edX, and ACTE.

    While having an artificial intelligence certification can improve your job prospects and increase your competitiveness in the job market, it does not guarantee employment on its own. Your job prospects ultimately depend on various factors, including your experience, skills, education, networking, and the demand for AI professionals in the industry. However, certification can significantly enhance your qualifications and make you more attractive to employers seeking AI talent.

    Yes, you can pursue multiple artificial intelligence course certifications to broaden your skill set, specialize in different areas of AI, and increase your marketability in the job market. Pursuing multiple certifications demonstrates your commitment to continuous learning and professional development, and allows you to acquire expertise in various AI technologies, methodologies, and applications.

  • Machine Learning Engineer
  • Data Scientist
  • AI Researcher
  • Natural Language Processing (NLP) Engineer
  • Computer Vision Engineer
  • AI Software Developer
  • AI Consultant
  • AI Product Manager
  • Robotics Engineer
  • Business Intelligence Analyst
  • AI Ethics Specialist

    • Yes, many artificial intelligence certification exams offer an online version that allows candidates to take the exam remotely from their own computers. Online proctoring services ensure the integrity and security of the testing process by monitoring candidates via webcam and screen sharing.

    While real-world experience can be beneficial for earning an artificial intelligence certification, it is not always a strict requirement. Certification programs typically focus on assessing knowledge and skills in AI concepts, techniques, and tools, rather than practical experience. However, having hands-on experience with AI projects and applications can enhance your understanding and readiness for certification exams.

    The worth of an ACTE artificial intelligence certification depends on various factors, including the reputation of the certification program, the relevance of the skills learned, and the demand for certified professionals in the job market. ACTE is a reputable training institute known for providing high-quality education and industry-relevant certifications. An artificial intelligence certification from ACTE can enhance your qualifications, improve job prospects, and validate your expertise in AI technologies. However, it's essential to research and evaluate the specific certification program to ensure it aligns with your career goals and objectives.

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    The Preferred Partner for 100+ Organizations' Hiring

    Learn from the certified and real time working professionals.

    • Over 100 firms that are looking for top talent for their open positions have come to rely on ACTE as their go-to partner.

    • Businesses have confidence in our ability to match them with the best individuals because of our considerable expertise and proven track record of success.

    • In this section, we'll examine the primary elements influencing this trust and examine how our constant commitment to excellence regularly results in remarkable results for our clients.

    Corporate Clients

    Artificial Intelligence Course Duration and Fees

    Level Course Duration Fees Structure
    Basic 1 - 1.5 Months ₹7,000 - ₹9,000
    Advanced 1.5 - 2 Months ₹7,000 - ₹10,000

    Job Opportunities in Artificial Intelligence

    Artificial Intelligence is preferred by more than 35% of developers. The most widely used and in-demand programming language in the tech industry is Artificial Intelligence.

    Salary In Artificial Intelligence
    Reach Our Placement Officer

    You can Work as a

    AI Product ManagerAI Ethics SpecialistAI ArchitectAI TrainerAI Curriculum DeveloperAI Project ManagerData Engineer

    Upcoming In-Demand Jobs

    Data AnalystData ScientistAI ProgrammerAI Systems EngineerAI Software Developer

    Student Testimonials

    Rogan Fresher

    AI Research Scientist | Hyderabad

     Got 7 LPA Package

    More Details : The instructors were highly knowledgeable and experienced in the field of artificial intelligence, guiding me through complex concepts with clarity and patience. I am grateful to ACTE for equipping me with the skills and mindset required to excel in my career.

    Vinusha Fresher

    Deep Learning Engineer | Chennai

     Got 10 LPA Package

    More Details :ACTE Training Institute played a pivotal role in my career journey from a fresher to a Deep Learning Engineer.The hands-on projects and real-world applications allowed me to gain practical experience and build a strong portfolio. Thanks to ACTE, I am now confident in my abilities as a Deep Learning Engineer and ready to take on new challenges in the industry.

    Mohana Fresher

    Robotics Engineer | Bengalure

     Got 8 LPA Package

    More Details : Transitioning from a fresher to a Robotics Engineer was made possible by the exceptional training I received at ACTE Training Institute. I am grateful to ACTE for equipping me with the skills and confidence to pursue a successful career as a Robotics Engineer.

    100% Placement

    7000+ Placed Student

    600+ Hiring Partners

    5.5 LPA Average Salary

    Recently Placed Students

    Akshara
    Sree Lakshmi
    John
    Vishali

    Artificial Intelligence Training FAQ's

    Boost Your Coding Ability: Essential Artificial Intelligence Training for Novices and Experienced

    Artificial Intelligence (AI) refers to the simulation of human intelligence in machines programmed to mimic cognitive functions such as learning, problem-solving, decision-making, and perception. AI encompasses a broad range of technologies and applications, including machine learning, natural language processing, computer vision, robotics, and expert systems. Its goal is to enable machines to perform tasks that typically require human intelligence, with the potential to analyze complex data, adapt to changing environments, and make autonomous decisions.

  • Enhancing efficiency and productivity
  • Enabling innovation and problem-solving
  • Improving decision-making
  • Enhancing user experiences
  • Driving economic growth
  • Machine Learning
  • Neural Networks
  • Natural Language Processing (NLP)
  • Computer Vision
  • Robotics
  • Proficiency in one or more programming languages, such as C++, Java, R, or Python.
  • Strong background in statistics and mathematics, particularly probability theory, calculus, and linear algebra.
  • Knowledge of machine learning methods and algorithms, such as reinforcement learning, unsupervised learning, and supervised learning.
  • Familiarity with feature engineering, data preparation, and model assessment methods.
  • Knowledge of AI frameworks and libraries, including PyTorch, TensorFlow, scikit-learn, and Keras.
  • Analytical thinking, problem-solving abilities, and the capacity to examine intricate information and come up with original solutions.
  • Domain knowledge in particular fields, such as robotics, computer vision, or natural language processing.
  • TensorFlow
  • PyTorch
  • scikit-learn
  • Keras
  • OpenCV
  • NLTK (Natural Language Toolkit)
  • Problem Definition
  • Data Collection and Preparation
  • Model Development
  • Evaluation and Validation
  • Deployment and Integration
  • Monitoring and Maintenance
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    Online Artificial Intelligence training refers to educational programs or courses that are delivered over the internet, allowing learners to access instructional materials, lectures, assignments, and interactive exercises remotely. These training programs cover various aspects of artificial intelligence, including machine learning, neural networks, natural language processing, computer vision, and robotics.

  • Flexibility
  • Accessibility
  • Variety of Courses
  • Cost-Effectiveness
  • Interactive Learning
  • Convenience
  • Accessibility
  • Flexibility
  • Resources
  • Skill Development
  • Networking Opportunities
  • Reputation and Accreditation
  • Curriculum
  • Instructor Expertise
  • Format and Delivery
  • Reviews and Testimonials
  • Support and Resources

    • Online Artificial Intelligence training can be effective for beginners, provided that the course is well-designed, structured, and accessible. Beginners can benefit from introductory courses that provide a foundational understanding of Artificial Intelligence concepts, algorithms, and techniques. These courses typically cover topics such as machine learning basics, data preprocessing, model building, and evaluation. Additionally, online training platforms often offer resources such as video tutorials, interactive exercises, and community forums to support beginner learners in their educational journey.

  • Set Clear Goals
  • Manage Your Time
  • Stay Organized
  • Actively Participate
  • Practice Regularly
  • Seek Support
  • Stay Motivated
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  • Working with datasets
  • Building and training models
  • Experimentation and optimization
  • Project work
  • Performance improvements
  • Project outcomes
  • Employee feedback
  • Business impact
  • Long-term benefits
  • Instructor guidance
  • Training materials
  • Hands-on labs
  • Peer collaboration
  • Continued learning
  • Introductory courses
  • Intermediate and advanced tracks
  • Customized learning paths
  • Number of participants
  • Customization
  • Training format
  • Additional services
  • Equipping employees with cutting-edge skills and knowledge in AI technologies, enabling them to develop innovative solutions, products, and services that differentiate the organization in the market.
  • Fostering a culture of continuous learning and skill development, empowering employees to adapt to technological advancements, industry trends, and changing customer needs.
  • Attracting and retaining top talent by offering opportunities for professional growth, career advancement, and specialization in high-demand areas such as Artificial Intelligence.
  • Accelerating digital transformation initiatives by building internal expertise in AI, driving process automation, data-driven decision-making, and customer-centric innovation.
  • Enhancing organizational agility and resilience by cultivating a workforce capable of leveraging AI capabilities to respond effectively to market disruptions, competitive pressures, and evolving business requirements.
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