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 refers to the development of intelligent machines that can perform tasks typically requiring human intelligence. It involves creating systems and algorithms capable of autonomous learning, reasoning, and decision-making, simulating human-like intelligence.
Examples of AI in daily life:
Advantages:
Artificial Intelligence (AI) is a broader concept that encompasses the development of intelligent systems capable of 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 explicit programming. ML algorithms enable systems to automatically learn patterns and make predictions based on the data they are exposed to.
A career in AI typically requires a strong educational background in computer science, mathematics, or related fields. The following qualifications can be beneficial:
The AI Engineer Course provides comprehensive training in Artificial Intelligence (AI). It focuses on developing practical skills and knowledge in areas such as machine learning, deep learning, natural language processing, computer vision, and AI deployment techniques. Participants learn to build AI models, analyze data, and apply AI algorithms to solve real-world problems. The course includes theoretical concepts, hands-on exercises, and practical projects for a well-rounded learning experience.
The AI Expert Course is an advanced program that allows participants to deepen their expertise in specific AI areas. It covers advanced AI algorithms, emerging trends, cutting-edge research, and complex applications. The course aims to equip participants with the knowledge and skills required to tackle complex AI challenges, develop innovative solutions, and push the boundaries of AI technology. Specialized modules or tracks focusing on topics like deep learning, computer vision, natural language processing, or reinforcement learning are often included.
To transition into an AI career from a different field, consider the following steps:
Pursuing a career in artificial intelligence is indeed a promising choice. The demand for AI professionals is rapidly increasing in diverse industries such as healthcare, finance, e-commerce, and technology. With continuous advancements in AI technology and widespread adoption, there are abundant opportunities for individuals to make significant contributions and have a meaningful impact in this field.
Python is considered one of the most suitable programming languages for AI development. It offers a wide range of libraries and frameworks, such as TensorFlow, PyTorch, and scikit-learn, that facilitate AI tasks like machine learning, deep learning, and natural language processing. Python's simplicity, readability, and vast community support make it popular among AI practitioners.
Comparing the advantages of AI and ML is subjective as they are closely related and often used together. However, some general points can be considered:
DataMites provides Artificial Intelligence certifications in Imphal, including AI Engineer Certification, Certified NLP Expert Certification, AI Expert Certification, AI Foundation Certification, and AI for Managers Certification.
The duration of the Artificial Intelligence course in Imphal provided by DataMites varies depending on the specific course chosen. The duration can range from one month to a year, with flexible training options available on weekdays and weekends.
Individuals can gain knowledge in Artificial Intelligence through self-study using online resources, enrolling in AI courses or degree programs, attending workshops or conferences, engaging in practical projects, and gaining hands-on experience.
The AI Engineer Course offered by DataMites in Imphal aims to equip individuals with the skills and knowledge required to become proficient AI engineers. The course covers various aspects of AI, including machine learning, deep learning, natural language processing, computer vision, and AI deployment techniques.
The Certified NLP Expert course offered by DataMites in Imphal focuses on Natural Language Processing (NLP) skills and applications. The course covers topics such as text preprocessing, sentiment analysis, named entity recognition, topic modeling, language generation, and neural network-based NLP models.
The AI for Managers Course provided by DataMites in Imphal covers topics such as AI fundamentals, machine learning, deep learning, natural language processing, computer vision, AI implementation challenges, ethical considerations, and AI project management. The course aims to provide managers with the necessary knowledge to make informed decisions regarding AI adoption and implementation.
The AI Foundation Course offered by DataMites in Imphal provides a comprehensive introduction to AI. The course covers the basics of AI, machine learning, and deep learning. Topics include supervised and unsupervised learning, neural networks, deep learning algorithms, model evaluation, and deployment techniques.
Generally, individuals with an interest in pursuing a career in Artificial Intelligence are eligible to enroll in an Artificial Intelligence Certification Training in Imphal. There are typically no strict prerequisites in terms of educational background or prior experience.
The average salary for an Artificial Intelligence Engineer in Imphal may vary based on factors such as experience, skills, industry, and the specific organization. However, an approximate average annual salary for an AI Engineer in India is around ?9,44,075.
To ensure a smooth process for issuing the participation certificate and booking the certification exam, participants are required to bring valid photo identification proofs, such as a National ID card or driving license, as proof of identity during the training session at DataMites in Imphal.
The cost of the Artificial Intelligence Training program at DataMites in Imphal depends on the particular course selected and the duration of the program. Typically, the fee for the Artificial Intelligence course in Imphal varies from INR 60,795 to INR 154,000. For accurate and detailed information about the fee structure, it is advisable to contact DataMites directly, as it may vary based on specific course offerings and features.
In the event that participants are unable to attend a session during the Artificial Intelligence training at DataMites in Imphal, they can coordinate with instructors to schedule a makeup class at a convenient time. For online training, recorded sessions will be provided to allow participants to catch up on missed content.
Yes, it is possible to attend a free demo class before enrolling in the Artificial Intelligence course at DataMites in Imphal. The demo class serves as an introduction to the training program, allowing potential participants to get an overview of the content, teaching methodology, and overall learning experience. Attending a demo class helps individuals make an informed decision about whether to enroll in the course.
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.