Instructor Led Live Online
Self Learning + Live Mentoring
In - Person Classroom Training
The entire training includes real-world projects and highly valuable case studies.
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
MODULE 1 : DATA SCIENCE COURSE INTRODUCTION
MODULE 2 : DATA SCIENCE ESSENTIALS
MODULE3 : DATA SCIENCE DEMO
MODULE 4 : ANALYTICS CLASSIFICATION
MODULE 5 : DATA SCIENCE AND RELATED FIELDS
MODULE 6 : DATA SCIENCE ROLES & WORKFLOW
MODULE 7 : MACHINE LEARNING INTRODUCTION
MODULE 8 : DATA SCIENCE INDUSTRY APPLICATIONS
MODULE 1 : PYTHON BASICS
MODULE 2 : PYTHON CONTROL STATEMENTS
MODULE 3 : PYTHON DATA STRUCTURES
MODULE 4 : PYTHON FUNCTIONS
MODULE 5 : PYTHON NUMPY PACKAGE
MODULE 6 : PYTHON PANDAS PACKAGE
MODULE 1 : OVERVIEW OF STATISTICS
MODULE 2 : HARNESSING DATA
MODULE 3 : EXPLORATORY DATA ANALYSIS
MODULE 4 : HYPOTHESIS TESTING
MODULE 5 : CORRELATION AND REGRESSION
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: PYTHON NUMPY & PANDAS PACKAGE
MODULE 3: VISUALIZATION WITH PYTHON
MODULE 4: ML ALGO: LINEAR REGRESSSION
MODULE 5: ML ALGO: KNN
MODULE 6: ML ALGO: LOGISTIC REGRESSION
MODULE 7: PRINCIPLE COMPONENT ANALYSIS (PCA)
MODULE 8: ML ALGO: K MEANS CLUSTERING
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: ML ALGO: LINEAR REGRESSION
MODULE 3: ML ALGO: LOGISTIC REGRESSION
MODULE 4: ML ALGO: KNN
MODULE 5: ML ALGO: K MEANS CLUSTERING
MODULE 6: PRINCIPLE COMPONENT ANALYSIS (PCA)
MODULE 7: ML ALGO: DECISION TREE
MODULE 8 : ML ALGO: NAÏVE BAYES
MODULE 9: GRADIENT BOOSTING, XGBOOST
MODULE 10: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
MODULE 11: ARTIFICIAL NEURAL NETWORK (ANN)
MODULE 12: ADVANCED ML CONCEPTS
MODULE 1: TIME SERIES FORECASTING - ARIMA
MODULE 2: FEATURE ENGINEERING
MODULE 3: SENTIMENT ANALYSIS
MODULE 4: REGULAR EXPRESSIONS WITH PYTHON
MODULE 5: ML MODEL DEPLOYMENT WITH FLASK
MODULE 6: ADVANCED DATA ANALYSIS WITH MS EXCEL
MODULE 7: AWS CLOUD FOR DATA SCIENCE
MODULE 8: AZURE FOR DATA SCIENCE
MODULE 1: DATABASE INTRODUCTION
MODULE 2: SQL BASICS
MODULE 3: DATA TYPES AND CONSTRAINTS
MODULE 4: DATABASES AND TABLES (MySQL)
MODULE 5: SQL JOINS
MODULE 6: SQL COMMANDS AND CLAUSES
MODULE 7: DOCUMENT DB/NO-SQL DB
MODULE 1: GIT INTRODUCTION
MODULE 2: GIT REPOSITORY and GitHub
MODULE 3: COMMITS, PULL, FETCH AND PUSH
MODULE 4: TAGGING, BRANCHING AND MERGING
MODULE 5: UNDOING CHANGES
MODULE 6: GIT WITH GITHUB AND BITBUCKET
MODULE 1: BIG DATA INTRODUCTION
MODULE 2: HDFS AND MAP REDUCE
MODULE 3: PYSPARK FOUNDATION
MODULE 4: SPARK SQL and HADOOP HIVE
MODULE 5: MACHINE LEARNING WITH SPARK ML
MODULE 6: KAFKA and Spark
MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION
MODULE 2: BI WITH TABLEAU: INTRODUCTION
MODULE 3 : TABLEAU: CONNECTING TO DATA SOURCE
MODULE 4 : TABLEAU : BUSINESS INSIGHTS
MODULE 5 : DASHBOARDS, STORIES AND PAGES
MODULE 6 : BI WITH POWER-BI
MODULE 1: ARTIFICIAL INTELLIGENCE OVERVIEW
MODULE 2: DEEP LEARNING INTRODUCTION
MODULE 3: TENSORFLOW FOUNDATION
MODULE 4: COMPUTER VISION INTRODUCTION
MODULE 5: NATURAL LANGUAGE PROCESSING (NLP)
MODULE 6: AI ETHICAL ISSUES AND CONCERNS
MODULE 1: NEURAL NETWORKS
MODULE 2: IMPLEMENTING DEEP NEURAL NETWORKS
MODULE 3: DEEP COMPUTER VISION - CNN
MODULE 4 : RECURRENT NEURAL NETWORK
MODULE 5: NATURAL LANGUAGE PROCESSING (NLP)
MODULE 6: REINFORCEMENT LEARNING
MODULE 7: DEEP REINFORCEMENT LEARNING
MODULE 8: GENERATIVE ADVERSARIAL NETWORK (GAN)
MODULE 9: DEPLOYING DL MODELS IN THE CLOUD (AWS)
Artificial Intelligence (AI) is a broader concept that encompasses the development of intelligent systems that can perform tasks requiring human intelligence. Machine Learning (ML), on the other hand, is a subset of AI that focuses on enabling systems to learn and improve from data without being explicitly programmed. ML algorithms allow systems to automatically learn patterns and make predictions based on the data they are exposed to.
Artificial Intelligence refers to the development of intelligent machines that can perform tasks requiring human intelligence. It involves creating systems and algorithms that can autonomously learn, reason, and make decisions, resembling human-like intelligence.
Instances of AI in daily life include virtual assistants like Siri, Alexa, and Google Assistant, recommendation systems used by streaming platforms and e-commerce websites, email spam filters, autonomous vehicles and self-driving cars, facial recognition technology in smartphones, and natural language processing in chatbots and customer support systems.
Advantages: Automation of repetitive tasks, increased accuracy and precision in decision-making, ability to handle large amounts of data, and enhanced capabilities in various industries.
Disadvantages: Job displacement due to automation, ethical concerns related to privacy and bias, dependency on AI systems, and high development costs.
A strong educational background in computer science, mathematics, or a related field is typically required. This includes bachelor's or master's degrees in AI or computer science, proficiency in programming languages, understanding of algorithms and statistics, and familiarity with machine learning and deep learning concepts.
The AI Engineer Course provides comprehensive training in AI, covering machine learning, deep learning, natural language processing, computer vision, and AI deployment techniques. Participants learn to build AI models, analyze data, and solve real-world problems through theoretical concepts, hands-on exercises, and practical projects.
The AI Expert Course is an advanced-level program that focuses on advanced AI algorithms, emerging trends, research, and complex applications. It offers specialized modules in areas such as deep learning, computer vision, natural language processing, or reinforcement learning.
To transition into an AI career from a different field, individuals can assess their existing skills, gain foundational knowledge through online courses, build practical projects, network with AI professionals, consider further education or certifications, seek entry-level positions, and continuously update skills in line with AI advancements.
Job roles in AI include AI Engineer/Developer, Machine Learning Engineer, Data Scientist, AI Research Scientist, NLP Engineer, Computer Vision Engineer, Robotics Engineer, AI Project Manager, and AI Consultant.
Yes, artificial intelligence is considered a promising career choice due to the increasing demand for AI professionals in various industries. Staying updated with advancements is essential in this evolving field.
Steps to start a career in AI include gaining a strong foundation in relevant subjects, pursuing education or certifications, acquiring knowledge in machine learning and deep learning, building a portfolio, seeking practical experience, continuous learning, networking, and considering advanced education or specialized certifications.
Python is considered a highly suitable programming language for AI development due to its extensive libraries and frameworks supporting machine learning, deep learning, and natural language processing. Python's simplicity and community support make it popular among AI practitioners.
Comparing the advantages of AI and ML is subjective, as they are closely related. AI allows machines to exhibit human-like intelligence, while ML focuses on algorithms that learn from data. Both AI and ML have numerous applications and offer significant benefits in various domains, such as healthcare, finance, and automation.
DataMites provides certifications in Gandhinagar from respected organizations such as IABAC, JAINx, and NASSCOM FutureSkills Prime, validating skills and enhancing credibility in the field of AI.
The duration of the Artificial Intelligence Course in Gandhinagar offered by DataMites varies depending on the specific course chosen, ranging from one month to a year. Flexible training options are available on both weekdays and weekends.
Knowledge in the field of Artificial Intelligence can be acquired through self-study using online resources, enrolling in AI courses in Gandhinagar, pursuing formal education, attending workshops and conferences, and gaining hands-on experience through practical projects.
The Certified NLP Expert course offered by DataMites in Gandhinagar focuses on Natural Language Processing (NLP) skills and applications. It covers topics such as text preprocessing, sentiment analysis, named entity recognition, topic modeling, language generation, and neural network-based NLP models.
The Artificial Intelligence for Managers Course provided by DataMites in Gandhinagar covers topics such as AI basics, machine learning, deep learning, natural language processing, computer vision, AI implementation challenges, ethical considerations, and AI project management.
The purpose of the AI Engineer Course provided by DataMites in Gandhinagar is to equip individuals with the necessary skills and knowledge to become proficient AI engineers. This course covers various aspects of AI, including machine learning, deep learning, natural language processing, computer vision, and AI deployment techniques, through hands-on projects and case studies.
The AI Foundation Course in Gandhinagar at DataMites provides a comprehensive introduction to AI, covering the basics of AI, machine learning, and deep learning. It includes topics such as supervised and unsupervised learning, neural networks, deep learning algorithms, model evaluation, and deployment techniques.
Anyone interested in pursuing a career in Artificial Intelligence can enroll in an Artificial Intelligence Certification Training in Gandhinagar. There are generally no strict prerequisites in terms of educational background or prior experience.
The average salary for an Artificial Intelligence Engineer in Gandhinagar may vary based on factors such as experience, skills, industry, and the specific organization. The exact figure without specific data for Gandhinagar is difficult to provide. However, according to Glassdoor, the average annual salary for an AI Engineer in India is approximately INR 9,44,075.
Yes, DataMites allows individuals to attend a free demo class before enrolling in the Artificial Intelligence Training in Gandhinagar. This provides potential participants with an opportunity to get an overview of the training program, its content, teaching methodology, and the overall learning experience. The demo class serves as an introductory session to help individuals make an informed decision about enrolling in the Artificial Intelligence course at DataMites.
The fee for the Artificial Intelligence Training program at DataMites in Gandhinagar may vary based on factors such as the specific course chosen and the duration of the program. Generally, the fee for the Artificial Intelligence course in Gandhinagar ranges from INR 60,795 to INR 154,000. The exact fee structure can be obtained from DataMites based on the specific course and its offerings.
Valid photo identification proofs, such as a National ID card or driving license, are required during the Artificial Intelligence Classes in Gandhinagar at DataMites for authentication purposes and to issue the participation certificate and book the certification exam.
In case of inability to attend a session during the Artificial Intelligence training at DataMites in Gandhinagar, participants can schedule a makeup class with instructors or access recorded sessions for online training to catch up on missed content and ensure a comprehensive learning experience.
Yes, DataMites offers Artificial Intelligence Courses in Gandhinagar that include placement assistance. Their Placement Assistance Team (PAT) supports students in various aspects of the job search process, including job connections, resume creation, conducting mock interviews, and facilitating discussions on interview questions. The aim is to assist participants in securing employment opportunities in the field of Artificial Intelligence by providing guidance and resources throughout the placement process.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.