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Advanced Diploma in AI and Ml
Eager to modify your capabilities with data-driven insights? Whether you’re a beginner or an experienced data professional, this integrated AI, ML, and data analytics program is tailored for you. AI, Machine Learning, and Data analytics are the core drivers of innovation, informed decision-making, and effective problem-solving across a wide spectrum of industries. Certification in AI and ML is an integrated program specifically structured to provide you with the essential understanding and hands-on skills necessary to excel as a capable data-driven professional. Upon completion of this program, you’ll gain the ability to integrate these technologies into your professional endeavors or establish a career in this highly sought-after domain. Through the comprehensive learning experience at Win in Life Academy, your journey commences with the foundational principles of data acquisition, cleansing, and interpretation, progresses into the captivating realm of machine learning algorithms.
Program Details
Key Takeaways
- Comprehensive Data Mastery: Develop a comprehensive hold of the data journey, including collection, cleaning, analysis, and the creation and assessment of AI and ML models.
- Hands-on Tool Expertise: Acquire practical skills using significant tools and methodologies in Python, machine learning, deep learning frameworks, and effective deployment techniques.
- Real-World Solution Application: Learn to apply AI, ML, and data analytics to solve tangible problems, derive valuable insights, and facilitate data-driven strategic choices.
- High-Growth Career Readiness: Obtain the crucial skills sought after in the expanding AI, machine learning, and data analytics sectors, boosting your career prospects.
Learner Profile
- Acquire a comprehensive understanding of basic AI and ML concepts, algorithms, and statistical principles.
- Build practical proficiency in Python, essential AI and ML libraries (like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch), and cloud platforms for model creation and deployment.
- Learn to derive meaningful insights from data, construct predictive models, and automate analytical workflows for efficiency.
- Grasp the ethical implications of AI and learn to design and implement AI systems responsibly and ethically.
- Investigate how AI and ML are revolutionizing various sectors such as finance, healthcare, retail, and manufacturing.
- Learn to leverage Certification in AI and ML insights to anticipate future industry shifts and make well-informed strategic business decisions.
- Understand the legal, regulatory, and ethical frameworks governing AI ML implementation within specific industry contexts.
- Gain practical experience working with real-world industry datasets and learn to extract valuable insights for practical applications.
- Master the complete lifecycle of developing, deploying, and maintaining robust AI and ML models in real-world production environments.
- Learn to evaluate model performance rigorously, identify areas for enhancement, and optimize models for practical, real-world use cases.
- Utilize AutoML tools and other advanced techniques to streamline AI ML development processes and accelerate innovation cycles.
- Stay informed about the latest breakthroughs in AI ML certification and cultivate the adaptability to embrace emerging technologies.
Benefits of Enrolling in Certification in AI and ML
Enrolling in a certificate in Artificial Intelligence and Machine Learning offers many advantages in today’s rapidly evolving technological landscape. This certification program provides structured learning, validates your skills, and improves your career prospects in a high-demand field.
- Natural Language Processing (NLP): This specialization focuses on enabling computers to understand, interpret, and generate human language. It involves techniques for tasks like text analysis, machine translation, and chatbot development, bridging the gap between human and machine communication.
- Computer Vision: This area deals with enabling computers to "see" and interpret visual information from the world, such as images and videos. Applications include image recognition, object detection, autonomous driving, and medical image analysis, enabling machines to extract meaningful insights from visual data.
- Deep Learning: This specialization explores artificial neural networks with multiple layers (deep neural networks) to learn complex patterns from large amounts of data. It has achieved significant breakthroughs in areas like image and speech recognition, natural language processing, and reinforcement learning, enabling more sophisticated AI applications.
I'm Interested in this program?
Certification in AI and ML Course
Upon completion of a certificate in artificial intelligence and machine learning, you will obtain a globally recognized certification from Win in Life Academy.
Globally Recognised Certification
Educational Board of Vocational Training and Research
Note: To secure certification in AI and ML, you must successfully complete the training from Win in Life Academy.
Tools to be Covered in Certification in AI and ML
mlFlow
Python
Docker
ChatGPT
ChatGPT
TensorFlow
AWS
tableau
Microsoft Excel
Rest-API
Power BI
R Language
NumPY
Zapier
Disclaimer: The tools, software, platforms, and datasets featured within this AI and ML Certification program are provided exclusively for instructional purposes to aid in the acquisition and comprehension of relevant concepts and methodologies. They are not intended nor optimized for deployment in actual production settings.
These resources may possess restricted features, evaluation licenses, or tailored setups for educational application and might carry inherent risks like data corruption or system instability, for which we extend no assurances or guarantee concerning their operation, dependability, precision, or appropriateness beyond their educational illustration.
Master 20+ essential industry tools
AI ML Certification : Course Curriculum
Expert Designed Certification in AI and ML course for Students and Professionals
A robust Certification in AI and ML program, designed by experts, fuels your pathway to your dream job.
Pre AI and ML Course Curriculum
Modules
Non-Technical
Module 1
English Communication & Grammar
- Basics of Communication
- Grammar and Vocabulary
- Verbal Communication Skills
- Written Communication
- Non-verbal Communication
- Confidence and Public Speaking
- Professional Communication Etiquette
- Practical Application
- Continuous Learning
Module 2
Mock Interviews
(Practice Assessment Test)
- Personal Introduction
- Technical Skills
- Problem-Solving
- Behavioral Insights
- Industry Knowledge
- Hypothetical Scenarios
- Soft Skills
Module 3
Corporate Etiquette
- Making the Most of Meetings
- Dressing Right for the Workplace
- Being Respectful and Thoughtful at Work
- Keeping Your Workspace Clean and Organized
- Using Technology Responsibly
- Dining with Manners in Professional Settings
- Building Relationships Through Networking
- Best Practices for Virtual Meetings and Online
- Communication
- Managing Your Time and Meeting Deadlines
- Understanding and Respecting Cultural Differences
- Leaving a Job Gracefully
Module 4
Aptitude
Program Modules for Certification in AI and ML
This robust curriculum is crafted to guide you from basic data processing to sophisticated model building and evaluation. It's organized across ten modules to deliver a gradual and in-depth educational journey:
Module 1
- 3 weeks
Introduction & Python Programming
Master Python fundamentals, from setup to OOP, with practical projects, enabling proficiency in data manipulation, model deployment, and core AI and ML concepts.
- Why is Python Programming Emergent?
- Installing & Setting up Python on System
- What are Variables & Uses of Variables?
- Python Revisit: Keywords, Data Types, Operators
- Decision Making
- Looping
- User Defined Function
- Lambda Function
- Error Handling in Python
- Python Generators
- Python Modules: Usage and Installation
- Understanding the OOP of Python
- Project on Python
Skills Acquired
- Python Proficiency
- Problem-solving
- Data Visualization
- AI/ML Concepts
- Model Deployment
Highlights
Module 2
- 3 weeks
Statistics
Objective: A foundational module for PG Diploma in Al and ML certification courses covering key statistical concepts and techniques essential for data analysis and machine learning applications.
- Virtual Lab Setup (Kali Linux, Windows, Metasploitable) | Demo
- Introduction to Kali Linux Environment
- Linux File System | Demo
- Basic Linux Commands | Demo
- Configuring a Secure Lab Environment
- Probability Theory
- Data Distributions
- Statistical Inference
- Data Distributions
- Hypothesis Testing
Highlights
Module 3
- 3 weeks
Deep Learning
Objective: A detailed exploration of deep learning techniques, focusing on neural networks and their applications in PG Diploma in Al and ML Certification courses.
- Introduction of Deep Learning
- Types of Deep Learning
- How does D.L. come into Picture?
- What Is ANN?
- Skills acquired
- Neural Networks Design
- Model Training Techniques
- CNNs (Convolutional
- Neural Networks)
- RNNs (Recurrent Neural Networks)
- The Basic terminology- Layer, Weight, Biases, Activation
- function, Losses, Optimizers, Learning rate
- The concept of Forward propagation
- Backward Propagation
- ANN using TensorFlow
- Practical (Creation of ANN model for real Dataset)
- Deep Learning Frameworks
- Neural Networks Design
- Model Training Techniques
- Deep Learning Frameworks
- CNNs (Convolutional Neural Networks)
- RNNs (Recurrent Neural Networks)
Highlights
Module 4
- 3 weeks
Inferential Statistics
Objective: Learn how to draw conclusions from data using inferential statistics. Understand hypothesis testing, confidence intervals, and apply statistical tests like Z-test and Chi-square.
- What are Inferential Statistics?
- Null Hypothesis
- Alternative Hypothesis
- Confidence Interval
- Significance Value
- Real Industry Program of Inferential Statistics
- Hypothesis Problem
- Z – test with Proportion Problem
- Chi Square Test
- Hypothesis Testing
- Statistical Inference
- Z-test
- Chi-square test
- Confidence Interval calculations
Highlights
Module 5
- 3 weeks
NumPy
Objective: Master NumPy arrays for efficient data manipulation. Learn array creation, manipulation, data types, and perform arithmetic and statistical operations.
- Python NumPy Array
- Creating Accessing, Manipulating NumPy Array
- NumPy Data Types
- Array Attributes
- Data Operations
- Arithmetic and Statistical Methods
- Sort, Search, and Count
- Practical
- NumPy Array Manipulation
- Data Operations
- Statistical Methods
- Array Attributes
- Data Sorting and Searching
Highlights
Module 6
- 3 weeks
Pandas
Gain expertise in Pandas Series and Data Frames for data analysis. Learn data manipulation, file handling, grouping, and handling missing data.
- The Series and Data Frame
- Creating, Accessing, Manipulating Pandas Data
- Series and Data Frame Attributes & Basic Functions
- Excel Automation with OpenPyXL
- Statistical Functions; String Functions
- Logical Indexing; Sorting & Reindexing
- Merging, Joining & Concatenation of Data
- Pandas File Handling
- Grouping Data
- Function Application
- Missing Data & Treatment
- Practical
- Pandas Data Manipulation
- Data Analysis
- File Handling
- Data Grouping
- Missing Data Treatment
Highlights
Module 7
- 3 weeks
Python and MySQL Integration
Learn to connect Python to MySQL databases. Execute SQL queries, handle transactions, and retrieve data into Pandas Data Frames for further analysis.
- Installing and configuring MySQL Connector
- Connecting to a MySQL database from Python
- Executing SELECT, INSERT, UPDATE, DELETE queries Handling transactions.
- Retrieving data from MySQL into Pandas data frames, performing data manipulations using Python.
- MySQL Database Interaction
- SQL Query Execution
- Data Retrieval
- Transaction Handling
- Python-MySQL Integration
Highlights
Module 8
- 3 weeks
Code Optimization
Build integrated data dashboards using Python, Excel, and MySQL. Learn code optimization techniques and implement robust error handling.
- Integrating Python, Excel, and MySQL to create a data dashboard
- Using visualization libraries (Matplotlib, Seaborn)
- Connecting the application to MySQL for data storage
- Techniques for optimizing Python and SQL code
- Implementing robust error handling in Python and SQL
- Work on a comprehensive project integrating Python, Excel, and MySQL
- Evaluation Of a Model
- Practical
- Data Dashboard Development
- Code Optimization
- Error Handling
- Data Visualization
- Database Integration
Highlights
Module 9
- 3 weeks
Unsupervised Machine
Explore unsupervised learning with a focus on clustering theory and K-means clustering. Learn to identify patterns in unlabeled data.
- Clustering Theory
- K-means Clustering
- Practical
- Clustering Theory
- K-means Clustering
- Unsupervised Learning Techniques
- Pattern Recognition.
Highlights
Module 10
- 3 weeks
Capstone Project
Apply acquired AI/ML skills to a real-world problem, demonstrating end-to-end project execution, from data analysis to model deployment and evaluation.
- Project Conceptualization and Problem Definition
- Data Acquisition and Preprocessing
- Model Selection and Development
- Model Training and Optimization
- Deployment Strategies and Implementation
- Performance Evaluation and Reporting
- Team Collaboration and Project Management
- Presentation of Project Findings
- End-to-End AI/ML Project Execution
- Real-world Problem Solving
- Model Deployment and Evaluation
- Project Management and Collaboration
- Effective Communication of Technical Findings
Highlights
Our Distinctive Approach
We are providing a premier certification in AI and ML experience by integrating advance resources, a precisely structured syllabus, and mentorship from experienced domain specialists.
Practical Application & Industry-Relevant Projects
We emphasize hands-on learning via comprehensive applied projects, reinforcing conceptual knowledge and reflecting contemporary professional standards.
Expert Guidance from Top-Tier Professionals
Our educators offer profound insights and encourage analytical reasoning, guaranteeing your expertise aligns with the newest AI and ML innovations, setting a higher benchmark in education.
Career Growth & Professional Connections
Upon completing our certification, you gain entry to significant networking avenues and career support, enabling you to obtain influential positions and internships within the AI and ML sector.
Program Fees
New Batches Starts Every 15th & 30th
₹75,000 (*Incl. Taxes)
Note: 0% interest rates with no hidden cost
Programme Faculty
What's Unique About This Program?
Why is our Certification in AI ML the best choice?
Features
Industry-Focused Curriculum
Placement mentorship program
Corporate Etiquette Sessions
Capstone projects
LMS Course kit
EC Council collaboration
Recorded Video
1:1 Personalized Mentorship
Placement Mock Interviews
Interdisciplinary expertise
Industry Expert sessions
WILA
Institute 1
Institute 2
Institute 3
Success Stories
Graduate Perspectives
Win In Life’s AI and ML Course Accreditations
Best AI ML Courses training by experienced faculty and industry leaders in the form of pre recorded videos, projects, assignments and live interactive sessions
Connect with our graduates
Have questions? Reach out to our alumni!
Find WILA alumni profiles and know more about their career path, specialization and more.
Frequently Asked Questions (FAQs)
An Artificial Intelligence Certification can significantly enhance your career prospects in the rapidly growing AI field, validating your skills and knowledge to potential employers and demonstrating your commitment to professional development in artificial intelligence. It can also lead to higher earning potential and more specialized roles.
While specific prerequisites vary, most Artificial Intelligence Certification programs typically recommend a basic understanding of programming (preferably Python), fundamental mathematical concepts like linear algebra and calculus, and some familiarity with statistical principles to effectively grasp the core concepts of artificial intelligence.
Earning an Artificial Intelligence Certification can open doors to various exciting career paths, including AI Engineer, Machine Learning Engineer, Data Scientist specializing in AI, AI Research Scientist, Natural Language Processing (NLP) Engineer, and Computer Vision Engineer, depending on the program’s focus and your existing skills.
An AI ML Certification specifically focuses on the principles, algorithms, and applications of Artificial Intelligence and Machine Learning, providing in-depth knowledge in areas like data preprocessing, model building, evaluation, and deployment, unlike general IT certifications that cover a broader range of technology domains.
Upon completing an AI ML Certification, you can typically expect to understand the core concepts of both Artificial Intelligence and Machine Learning, be proficient in using relevant tools and libraries, be able to build and evaluate ML models for various tasks and understand the ethical considerations surrounding AI and ML applications.
Many introductory Certification in AI and ML program is designed for individuals with little to no prior experience, often starting with the fundamentals of programming, mathematics, and statistics before delving into AI and ML concepts. However, some programs may require a basic technical background.
An Online AI ML Certification offers greater flexibility in terms of learning schedule and location, allowing you to study at your own pace and fit learning around existing commitments. It often provides access to a wider range of instructors and resources globally and can sometimes be more cost-effective.
The quality and recognition of an Online AI ML Certification can be comparable to traditional programs, especially if the online program is offered by a reputable institution or industry-recognized organization with experienced instructors and a well-structured curriculum. It’s crucial to research the provider’s credibility.
Reputable Online AI ML Certification programs often provide various forms of support and interaction, including online forums for discussions, virtual office hours with instructors, opportunities for peer collaboration on projects, and access to technical support for any platform-related issues.
The duration of a Certificate in Artificial Intelligence and Machine Learning program can vary significantly, ranging from a few months to a year, depending on the program’s depth, intensity, and whether it’s pursued on a full-time or part-time basis.
A well-structured Certificate in Artificial Intelligence and Machine Learning program that includes hands-on projects, case studies, and practical exercises can equip you with valuable job-ready skills sought after by employers in the AI and ML domains, particularly for entry-level and junior roles.
In some cases, credits earned from a Certificate in Artificial Intelligence and Machine Learning from an accredited institution may be transferable towards a related degree program, such as a master’s in data science or Artificial Intelligence, but this depends on the specific policies of the degree-granting institution.
