Master Azure AI Engineer Course – AI-102 Certification Training

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12 Sessions
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26 Videos
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31 Notes
Quick Notes
29 Labs
Hands-on Labs
2 Project(s)
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8 Tests
Skill Tests
40 Guides
Interview Q&A

Azure AI Engineer Certification Training Overview

Azure AI Engineer Certification is a popular Certification for developers and data specialists who want to create smart, adaptable, and cloud-based projects using Microsoft Azure. As more companies start using AI to boost automation, enhance customer satisfaction, and make better choices, the need for skilled Azure AI Engineers is increasing quickly. Getting this credential through the AI-102 Certification proves your skills and helps you stand out in a tough job market.

ScholarHat’s Azure AI Engineer Course is designed to help you learn the necessary tools and methods for creating advanced AI solutions. You will get practical experience with Azure Cognitive Services, Azure Open AI, Azure Search Services, and other high-tech tools to develop real applications. Whether you are preparing for the Azure AI Engineer Exam, looking to improve your skills as an AI Engineer Associate, or thinking about new job options, this course provides organized lessons, expert help, and hands-on labs to make sure you're ready for the industry. 

Azure AI Engineer Course Objectives

  1. Boost Your AI-102 Skills - Learn the basics of Azure AI Engineer Associate Skills to design and build AI solutions that help businesses grow.
  2. Use Azure Cognitive Services - Use Azure Cognitive Services to make your apps smarter by recognizing images, understanding speech, and processing text.
  3. Create Smart Machine Learning Models - Use Azure AI Services to build and launch models that predict trends and solve problems.
  4. Understand Text with NLP - Understand and analyze text data using Azure Language Understanding (LUIS) and Text Analytics to make sense of information.
  5. Build Clever Chatbots - Create chatbots with Azure Bot Services that talk to users and work smoothly with business apps.
  6. Work with Images - Design computer vision solutions using Azure Custom Vision to recognize images and detect objects.
  7. Keep AI Safe - Secure your AI projects with Azure Active Directory and follow rules to make AI safe and fair.
  8. Make AI Workflows Simple - Use your own data to train and publish models easily.
  9. Check and Fix AI Apps - Track and improve your AI apps with Azure Monitor and Application Insights to keep them running smoothly.
  10. Get Ready for the AI-102 Exam - Prepare for the AI-102 Certification with hands-on labs, practice tests, and real-world examples to pass with confidence.

Why Become an Azure AI Engineer in 2025?

    1.) High Demand: 80% of enterprises now use AI. Azure holds a 30% share in cloud AI, creating strong job demand across finance, healthcare, retail, and more. (Gartner, 2024)

    2.) Attractive Compensation: Azure AI Engineers enjoy competitive salaries:

    • US: $100,000 - $150,000 per year.
    • India: 15,00,000 - 30,00,000 annually.

    3. Career Growth Opportunities: With the Azure AI Engineer Certification Training, you open the door to various career paths like Machine Learning Engineer, Data Scientist, and AI Solutions Architect in leading companies such as Microsoft, Google, and Amazon.

    4.) Work on Cutting-Edge Technologies: As AI and machine learning evolve, Azure AI Engineers work with the latest tools and technologies to innovate in industries like healthcare, finance, and e-commerce.

    5.) Job Stability and Growth: With AI expected to reach $407B by 2027, Azure AI jobs are growing 35% YoY, offering long-term stability and rapid career growth.

    Why Learn Azure AI?

    Azure AI Engineer Career Scope

    Azure AI Engineer
    AI Engineer
    Azure AI Architect
    AI Architect
    AI Lead
    ₹12 LPA
    Avg package
    35%
    Avg hike
    3,200+
    Transitions
    78%
    Demand
    Annual Salaries (₹)
    ₹15 LPA
    Avg package
    38%
    Avg hike
    3,200+
    Transitions
    75%
    Demand
    Annual Salaries (₹)
    ₹20 LPA
    Avg package
    40%
    Avg hike
    3,200+
    Transitions
    72%
    Demand
    Annual Salaries (₹)
    ₹24 LPA
    Avg package
    45%
    Avg hike
    3,200+
    Transitions
    75%
    Demand
    Annual Salaries (₹)
    ₹42 LPA
    Avg package
    80%
    Avg hike
    6,000+
    Transitions
    99%
    Demand
    Annual Salaries (₹)

    Tools and Technologies Covered

    Python
    Fast API
    Azure AI Services
    Azure Vision
    Azure Face API
    Azure Speech
    Language
    Translator
    Open AI
    Azure Q&A
    Azure Search
    VS Code

    Azure AI Engineer Certification Training Key Features

    • 6 Weeks of Intensive Live Training
    • Learn from Microsoft MVPs
    • Build real-world Projects
    • Career Coaching
    • Resume & Portfolio Building
    • Job Assistance

    Live Classes Schedule

    Our learn-by-building-project method enables you to build practical/coding experience that sticks. 95% of our learners say they have confidence and remember more when they learn by building real world projects.

    Azure AI Engineer Certification Training

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    Course Curriculum

    Python For AI Development

    Python Foundations

    1. Introduction to Python
    2. Variables and Data Types
    3. Operators
    4. Conditional Statements and Loops
    5. Functions & Classes
    6. Dictionaries and Sets
    7. Modules, Files

    Python Libraries

    1. Pandas
    2. Numpy
    3. Matplotlib
    4. Pydantic
    5. Uv Package manager
    6. Fast API
    7. Building REST API
    8. Database operations
    AI Foundations with Azure

    AI Foundations

    1. Introduction to AI
    2. Understanding Machine Learning
    3. Types of Machine Learning
    4. Introduction to Deep Learning
    5. Machine Learning vs Deep Learning
    6. Introduction to Gen AI
    7. Introduction to LLMs
    8. Azure AI Services Classification
    9. Azure AI Workloads & Capabilities
    10. Responsible AI Principles
    11. AI-102: Exam Overview & Details

    Working with Azure AI Services

    1. Steps to Setup Azure AI Services
    2. Azure AI Services Deployment Options
    3. Consuming Azure AI Services
    4. REST API Client
    5. SDK Client
    6. Securing Azure AI Services
    7. Manage Azure AI Costs
    Azure Cognitive Services

    Computer Vision with Azure

    1. Introduction to Azure Computer Vision
    2. Analyze Images Using Pre-Trained Models
    3. Detect and Analyze Faces
    4. Perform OCR on Documents and Images
    5. Image Classification with Custom Vision
    6. Analyze Video with Azure Video Indexer

    Natural Language Processing with Azure

    1. Azure AI Language Services Overview
    2. Text Analytics: Sentiment Analysis, Key Phrase Extraction
    3. Named Entity Recognition (NER)
    4. Language Detection and Translation
    5. Building QnA Solutions with Azure Language
    6. Custom Text Classification and Entity Recognition

    Document Intelligence with Azure

    1. Use Prebuilt Models to Analyze Common Documents
    2. Extract Data from Forms and Invoices
    3. Build Custom Models using Azure Document Intelligence
    4. Implement Document Processing Pipelines
    Azure Open AI and AI Search

    Azure OpenAI

    1. What is OpenAI?
    2. An overview of OpenAI model families
    3. Fine-Tuning GPT Models in Azure
    4. Retrieval-Augmented Generation
    5. Image Generation with DALL·E
    6. Understanding Prompt Design
    7. Principles of well-defined prompts

    Conversational AI with Azure Bot Services

    1. Introduction to Azure AI Search
    2. Core Components & Architecture
    3. Data Ingestion and Indexing Process
    4. Implementing Semantic Search
    5. Vector Search and Hybrid Retrieval
    6. Building Intelligent Search Apps
    ChatGPT and Github Copilot

    Working with ChatGPT

    1. Understanding OpenAI and ChatGPT
    2. How ChatGPT Works?
    3. Coding with ChatGPT
    4. Generating, optimizing, and debugging code
    5. Generating documentation and code explainability
    6. Translation among different programming languages

    GitHub Copilot

    1. What is GitHub Copilot?
    2. Setting up GitHub Copilot
    3. GitHub Copilot Basics and Features
    4. Debugging and optimization tips
    5. Testing and Debugging with GitHub Copilot

    Overview of Python
    Python Overview
    Preview 0h 02m 42s
    Python Advantages and Disadvantages
    Preview 0h 03m 51s
    Python an Interpreted Language
    0h 02m 15s
    Python History
    0h 03m 24s
    Downloading and Installing Python
    0h 04m 15s
    Python First Program
    Preview 0h 03m 53s
    Variables and Data Types
    Variables
    0h 06m 03s
    Data Types
    0h 07m 04s
    String and String Methods
    0h 06m 07s
    String Formatting
    0h 03m 09s
    Escapse Sequences
    0h 03m 32s
    Python Operators
    0h 07m 28s
    Reading from Keyboard
    0h 04m 36s

    Conditional Constructs
    Conditional Statements
    0h 01m 37s
    If Statement
    0h 03m 47s
    If else statement
    0h 02m 33s
    If-Elif-Else-Statement
    0h 03m 43s
    Nested Conditions
    0h 03m 42s
    Match-Case Conditions
    0h 02m 59s
    Looping Constructs
    Loops in Python
    0h 00m 44s
    For Loop
    0h 05m 50s
    While Loop
    0h 04m 23s
    Jump Statements
    0h 00m 53s
    Break Statement
    0h 02m 00s
    Continue Statement
    0h 03m 22s
    Return Statement
    0h 02m 28s
    1. Introduction to AI Workloads and Azure AI Capabilities
    0:07:00
    2. Scope and Objectives of the AI-102 Certification
    0:07:30
    3. Responsible AI Principles
    0:06:00
    4. Azure AI Content Safety
    0:08:00
    5. Monitoring AI for Bias and Drift
    0:08:00
    6. Creating and Consuming Azure AI Services
    0:05:30
    7. Securing AI Services
    0:06:00
    8. Monitoring and Logging with Application Insights
    0:08:00
    9. Integrating AI Services using CLI, SDKs, and REST APIs
    0:04:00
    10. Cost Management and Governance for AI Projects
    0:07:00
    11. Image Analysis with Prebuilt and Custom Vision Models
    0:08:00
    12. Object and Face Detection in Images
    0:09:00
    13. Optical Character Recognition (OCR) for Text Extraction
    0:06:00
    14. Video Analysis in Azure AI
    0:07:30
    15. Deploying Vision Models to Edge Devices
    0:05:00
    16. Text Analytics in Azure AI
    0:08:00
    17. Custom Text Classification and Entity Recognition
    0:06:30
    18. Conversational Language Understanding (CLU) in Azure AI
    0:06:00
    19. Text Translation and Language Detection in Azure AI
    0:06:00
    20. Speech-to-Text and Text-to-Speech Conversion in Azure AI
    0:07:30
    21. Custom Speech Model Training in Azure AI
    0:09:00
    22. Real-Time Captions and Speech Translation in Azure AI
    0:06:00
    23. Voice Synthesis using Custom Neural Voice (CNV) in Azure AI
    0:07:30
    24. Secure and Monitor Speech Services in Azure AI
    0:05:00
    25. Azure OpenAI Capabilities and Use Cases
    0:07:00
    26. Prompt Engineering and Fine-Tuning GPT Models in Azure AI
    0:09:30
    27. Retrieval Augmented Generation (RAG) in Azure AI
    0:08:30
    28. Image Generation using DALL·E in Azure AI
    0:06:00
    29. Azure AI Search Architecture and Components
    0:06:00
    30. Prebuilt and Custom Document Model Usage in Azure AI
    0:08:00
    31. Semantic and Vector Search Implementation in Azure AI
    0:05:30
    1. Azure AI: Exploring Form Recognition
    00:30:00
    2. Azure AI: Use an Azure AI Services Container
    00:45:00
    3. Azure AI: Read Text in Images
    01:00:00
    4. Azure AI: Deploy AI Search using Bicep
    00:30:00
    5. Azure AI: Translate Text with Azure AI Translator
    00:45:00
    6. Azure AI: Ubuntu Data Science VM ARM Template
    00:45:00
    7. Azure AI: AI Sensor Data Preprocessing using NumPy
    00:30:00
    8. Azure AI: Validate AI Configuration Input using Pydantic
    00:30:00
    9. Azure AI: Analyze Azure AI Service Logs with Pandas
    00:30:00
    10. Azure AI: Recognize and Synthesize Speech
    00:45:00
    11. Azure AI: Text Analysis with Azure AI Content Safety
    00:45:00
    12. Azure AI: Building Azure AI Health Bot using Azure CLI
    00:30:00
    13. Azure AI: Deploy AI Search using an ARM Template
    00:30:00
    14. Azure AI: Image Analysis with Azure AI Content Safety
    00:45:00
    15. Azure AI: Explore Computer Vision
    00:30:00
    16. Azure AI: Create a Knowledge Store with Azure AI Search
    01:00:00
    17. Azure AI: Multilingual Speech Translation
    00:45:00
    18. Azure AI: Pandas with Azure Text Analytics Results
    00:30:00
    19. Azure AI: Create a FastAPI Service for AI Translation
    00:30:00
    20. Azure AI: FastAPI Service for NumPy Model Predictions
    00:30:00
    21. Azure AI: Exploring Face Detection
    00:45:00
    22. Azure AI: Exploring Optical Character Recognition
    00:45:00
    23. Azure AI: Validate Input Text & Metadata with Pydantic
    00:30:00
    24. Azure AI: Preprocess Data & Send to Azure AI
    00:30:00
    25. Azure AI: Extract Data from Forms
    01:00:00
    26. Azure AI: Translate Speech using Azure AI Speech Service
    01:00:00
    27. Azure AI: Pydantic JSON Schema for Azure AI Settings
    00:30:00
    28. Azure AI: AI Image Captioning API with FastAPI
    00:30:00
    29. Azure AI: Detect and Analyze Faces
    01:00:00
    Project#1: Azure AI ChatGPT

    Building Intelligent Chatbots

    1. Introduction to Azure OpenAI Service
    2. Natural Language Capabilities of ChatGPT
    3. Understanding User Queries & Providing Accurate Responses
    4. Designing Human-like Conversational Flows
    5. Prompt Engineering for Contextual Responses
    6. Fine-Tuning ChatGPT for Industry-Specific Use Cases

    Enterprise-Ready Integration

    1. Integrating with Azure Cognitive Search (RAG)
    2. Accessing Company Documents, Databases & Policies
    3. Context-Aware & Accurate Answers
    4. Customizing Solutions for HR Support
    5. Chatbots for Customer Service
    6. Internal Knowledge Management with AI
    Project#2: Intelligent Resume Matcher

    AI-Powered Resume Matching

    1. Introduction to Resume Matcher with Azure AI Foundry
    2. Transforming Resumes into Numerical Embeddings
    3. Processing Job Descriptions using Embeddings
    4. Measuring Semantic Similarity between Candidates & Roles
    5. Ranking Candidates by Relevance (Beyond Keyword Matching)
    6. Ensuring Fair and Accurate Talent Evaluation

    Recruitment Efficiency & Impact

    1. Automated Shortlisting of Candidates
    2. Saving HR Teams Time in Initial Screening
    3. Reducing Manual Bias in Hiring
    4. Identifying High-Potential Candidates Faster
    5. Improving Hiring Efficiency & Quality of Talent Pipeline
    6. Building AI-Driven Tools for Modern Recruitment
    1. Introduction to Azure AI and Responsible AI
    15 Questions
    2. Azure AI Skill Test
    30 Questions
    3. Developing and Managing Azure AI Services
    15 Questions
    4. Computer Vision Solutions with Azure AI Vision
    15 Questions
    5. Natural Language Processing (NLP) with Azure AI Language
    15 Questions
    6. Speech Services with Azure AI
    15 Questions
    7. Generative AI with Azure OpenAI Service
    15 Questions
    8. Knowledge Mining with Azure AI Search
    15 Questions

    Q&A Guides

    Introduction to AI Workloads and Azure AI Capabilities
    00:17:00
    Scope and Objectives of the AI-102 Certification
    0:20:00
    Responsible AI Principles: Fairness, Safety, Privacy, Accountability
    00:18:00
    Azure AI Content Safety and Responsible Usage
    00:15:00
    Monitoring AI for Bias and Drift
    00:16:00

    Creating and Consuming Azure AI Services (Language, Vision, Speech, Search)
    00:17:00
    Securing AI Services (Authentication, Authorization, Network Security)
    00:13:00
    Monitoring and Logging with Application Insights
    00:19:00
    Integrating AI Services using CLI, SDKs, and REST APIs
    00:18:00
    Cost Management and Governance for AI Projects
    00:14:00

    Image Analysis with Prebuilt and Custom Vision Models
    00:16:00
    Object and Face Detection in Images
    0:20:00
    Optical Character Recognition (OCR) for Text Extraction
    00:15:00
    Video Analysis (Real-Time and Batch)
    00:13:00
    Deploying Vision Models to Edge Devices
    00:14:00

    Text Analytics: Sentiment, Key Phrases, Named Entities
    00:19:00
    Custom Text Classification and Entity Recognition
    00:16:00
    Conversational Language Understanding (CLU)
    00:13:00
    Question Answering with Azure AI Language
    00:18:00
    Text Translation and Language Detection
    0:20:00

    Speech-to-Text and Text-to-Speech Conversion
    00:18:00
    Custom Speech Model Training
    00:17:00
    Real-Time Captions and Speech Translation
    00:19:00
    Voice Synthesis using Custom Neural Voice (CNV)
    00:16:00
    Secure and Monitor Speech Services
    00:13:00

    Azure OpenAI Capabilities and Use Cases
    00:14:00
    Prompt Engineering and Fine-Tuning GPT Models
    00:18:00
    Building Apps with ChatGPT and GPT APIs
    00:13:00
    Retrieval Augmented Generation (RAG)
    00:15:00
    Image Generation using DALL·E
    0:20:00

    Azure AI Search Architecture and Components
    00:16:00
    Indexing Structured and Unstructured Data
    00:14:00
    AI Enrichment with Cognitive Skills
    00:19:00
    Semantic and Vector Search Implementation
    00:17:00
    Integration with Azure OpenAI for RAG
    00:18:00

    Planning Document Intelligence Solutions
    00:16:00
    Prebuilt and Custom Document Model Usage
    00:15:00
    Training and Testing Models with Sample Forms
    0:20:00
    Composing and Chaining Multiple Models
    00:14:00
    Large-Scale Document Processing
    00:19:00

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    Azure AI Engineer Certification

    Q1. What is the Azure AI Engineer Certification?

    Q2. Who should take the Azure AI Engineer Certification?

    Q3. What are the prerequisites for this certification?

    Q4. How much does the certification exam cost?

    Q5. What are the career benefits of this certification?

    Frequently Asked Questions

    Q1. How can I prepare for the Azure AI Engineer Certification?
    To prepare for the Azure AI Engineer Certification, you should: 1.) Study Microsoft’s official learning paths and take practice tests. 2.) Master Azure AI services like Cognitive Services and Azure Machine Learning. 3.) Participate in hands-on labs and real-world projects to strengthen practical skills. 4.) Consider enrolling in a training program for structured learning.
    Q2. How long is the certification valid?
    The Azure AI Engineer Certification is valid for two years. After that, you may need to renew it by taking the latest certification exam or completing the necessary training.
    Q3. How long is the exam, and what is the passing score?
    The AI-102 exam lasts for 150 minutes. The passing score is typically 700 out of 1000. However, the exact passing criteria may vary, so it's essential to check the official Microsoft exam page for updates.
    Q4. What job roles can I apply for after earning this certification?
    After earning the certification, you can pursue roles such as: 1.) Azure AI Engineer 2.) Machine Learning Engineer 3.) Data Scientist 4.) AI Solutions Architect 5.) AI Consultant or Cloud Developer specializing in AI solutions.
    Q5. How long does the Azure AI Engineer Certification Training take?
    The Azure AI Engineer Certification Training typically takes 6-8 weeks depending on your learning pace and whether you're taking the course full-time or part-time.
    Q6. Will I get hands-on experience during the training?
    Yes, most training programs offer hands-on labs where you can work on real-world projects and gain practical experience with Azure AI tools and services.
    Q7. What makes this training different from other AI certifications?
    This training focuses specifically on Microsoft Azure AI services, providing practical knowledge of tools like Azure Cognitive Services, Azure Machine Learning, and AI applications. The training also includes a certification exam preparation designed to help you succeed.
    Q8. What career growth can I expect after completing this training?
    After completing the training, you can expect to: 1.) Gain advanced skills in AI, improving job prospects. 2.) Open doors to higher-paying AI roles in top companies. 3.) Expand your career opportunities with a focus on Azure AI technologies and cloud solutions.
    Q9. What should I do after completing this certification?
    After completing the Azure AI Engineer Certification, consider: 1.) Applying for jobs in roles like AI Engineer or Machine Learning Engineer. 2.) Continuing to upskill by pursuing advanced certifications or learning about emerging AI technologies. 3.) Participating in AI communities and networking with industry professionals to stay updated on trends.
    Q10. Is the Azure AI Engineer certification worth pursuing in 2025?
    Yes, the Azure AI Engineer Associate certification is worth pursuing in 2025, especially if you’re aiming for roles in AI, machine learning, or data science. As companies continue to adopt Azure-based AI solutions, certified professionals are in demand for their proven skills and understanding of Microsoft’s AI tools.
    Q11. How much does the Azure AI Engineer certification cost?
    The exam (AI-102) costs around $165 USD, but prices may vary by location. Sometimes Microsoft or training partners offer discounts or vouchers, especially for students or professionals through learning programs.
    Q12. Is Azure Ai Engineer certification worth it?
    If you’re wondering whether the Azure AI Engineer certification is worth your time and effort, the short answer is: yes, absolutely! As AI continues to transform industries, companies are on the lookout for professionals who can build smart, scalable AI solutions-especially on platforms like Microsoft Azure. Getting certified not only boosts your credibility but also opens doors to exciting job opportunities and higher pay. Plus, it shows you’re serious about mastering cutting-edge AI tools that businesses rely on every day.
    Q13. What’s the Salary Like for an Azure AI Engineer?
    Let’s talk numbers! Azure AI Engineers are in high demand, and that demand reflects in their salaries. In the US, you can expect to earn anywhere from $120,000 to $160,000 a year, depending on your experience. In India, salaries typically range from ₹20 lakh to ₹50 lakh annually. And globally, Azure AI Engineers often earn more than their peers because they have specialized skills in one of the world’s leading cloud platforms. So yes, it’s definitely a lucrative career path!
    Q14. Is the AI-900 Exam Hard?
    If you’re new to AI or Azure, don’t worry-the AI-900 exam is designed to be beginner-friendly. It covers the basics of AI concepts and Azure’s AI services, so you don’t need to be an expert to pass. With some focused study and hands-on practice, most people find it very doable. It’s a great starting point if you want to build confidence before diving into more advanced certifications. Ready to kickstart your AI career with Azure? This certification could be your gateway to a future-proof, high-paying role in one of tech’s hottest fields!
    Q1. Can I Attend a Demo Session before Enrolment?
    Yes, you can Attend a Demo Session before Enrolment in angular certification course. It gives you the opportunity to assess whether the training program aligns with your learning objectives. So, don't hesitate! Take advantage of this opportunity and attend a demo session before making your decision.
    Q2. Can I request for a support session if I need to better understand the topics?
    Yes, of course you can request for a support session if you need to better understand the topics. For that, you need to be in touch with the counsellor. Contact on +91- 999 9123 502 or you can mail us at hello@scholarhat.com
    Q3. Who are your mentors?
    All our mentors are highly qualified and experience professionals. All have at least 8-10 yrs of development experience in various technologies and are trained by Dot Net Tricks to deliver interactive training to the participants.
    Q4. What If I miss my online training class?
    All online training classes are recorded. You will get the recorded sessions so that you can watch the online classes when you want. Also, you can join other class to do your missing classes.
    Q5. Can I share my course with someone else?
    In short, no. Check our licensing that you agree to by using ScholarHat LMS. We track this stuff, any abuse of copyright is taken seriously. Thanks for your understanding on this one.
    Q6. Do you provide any course material or live session videos?
    Yes we do. You will get access to the entire content including class videos, mockups, and assignments through LMS.
    Q7. Do you provide training on latest technology version?
    Yes we do. As the technology upgrades we do update our content and provide your training on latest version of that technology.
    Q8. Do you prepare me for the job interview?
    Yes, we do. We will discuss all possible technical interview questions and answers during the training program so that you can prepare yourself for interview.
    Q9. Will I get placement assistance after receiving my course completion certificate?
    Yes, you’ll get placement assistance after receiving your course completion certificate. The placement assistance provided by the US will guide you through the job search process, help you polish your resume, and connect you with potential employers. For that, you need to be in touch with the counsellor. Contact on +91- 999 9123 502 or you can mail us at hello@scholarhat.com
    Still have some questions? Let's discuss.
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