• Application closes on

    24 Dec, 2024

  • Program duration

    16 weeks

  • Learning Format

    Live, Online, Interactive

Why Join this Program

  • icons
    Earn an Elite Certificate

    Joint program completion certificate from Purdue University Online and Simplilearn

    Joint program completion certificate from Purdue University Online and Simplilearn

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    Leverage the Purdue Edge

    Become eligible for a membership at the Purdue University Alumni Association

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    Learn Popular No Code AI Tools

    Gain exposure to DataRobot, Dataiku, Amazon SageMaker Canvas, and other prominent tools

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    Career Support Services

    Enhance your resume and showcase your profile to recruiters with career assistance services

Take the first step to your goals

Lifetime access to self-paced e learning content

Corporate Training

Enterprise training for teams

No Code AI and Machine Learning Overview

This program enables you to master no-code AI and ML platforms, empowering you to perform data analysis, build models, and make data-driven decisions with ease. Gain hands-on experience with intuitive drag-and-drop interfaces, automated machine learning, and visual workflows.

Key Features

  • Simplilearn Career Service helps you get noticed by top hiring companies
  • Program completion certificate from Purdue University Online and Simplilearn
  • Access to Purdue's alumni association membership on program completion
  • 50+ hours of core curriculum delivered in live online classes by industry experts
  • Gain exposure to Amazon SageMaker Canvas, DataRobot, Dataiku, KNIME, and other prominent tools
  • Apply your knowledge through hands-on projects spanning various industries
  • Live online masterclasses delivered by Purdue faculty and staff
  • Dedicated add-on course on generative AI, prompt engineering and ChatGPT

No Code AI & ML Program Advantage

Gain a competitive edge with applied learning in the groundbreaking arena of no-code AI. This program enables you to make data-driven decisions using AI & ML without writing code, empowering you to build intelligent solutions with no-code platforms.

  • Program Certificate

    Partnering with Purdue University Online

    • Receive a joint Purdue-Simplilearn program certificate
    • Masterclasses delivered by Purdue faculty and staff
    • Become eligible for Purdue’s Alumni Association membership

No Code AI and Machine Learning Details

Gain a competitive edge through practical experience in the field of no-code AI and ML. Gain hands-on experience across diverse subjects such as data collection, data cleaning, and machine learning algorithms. Additionally, delve into advanced topics such as ensemble methods, SVM, ANNs, and NLP.

Learning Path

  • PG NC - Program Induction

    Get started with the No Code AI and Machine Learning Specialization, delivered jointly by Purdue University Online and Simplilearn. Kickstart your learning journey and explore the ability to build practical AI solutions using no-code tools.

  • PG NC - Fundamentals of AI & Machine Learning
    • Overview of AI & Machine Learning, and Their Importance
    • Machine Learning Life Cycle
    • Machine Learning Challenges
    • Introduction to MLOps
    • Introduction to No-Code AI & Machine Learning
    • Advantages and Limitations of No-Code AI & ML
    • Popular No-Code AI Platforms
    • Key Features of No-Code AI Platforms
    • Working with Data in No-Code AI Platforms
    • Building Models with No-Code Tools
  • PG NC - Data Collection, Cleaning and Preprocessing
    • Data Sources and Datasets
    • Data Acquisition Techniques
    • Assessing Data Completeness, Consistency, and Accuracy
    • Automated Data Collection Tools
    • Data Import and Preprocessing using No-Code Tools
    • No-Code Tools for Data Transformation
    • Data Visualization Techniques without Coding
    • Data Cleaning Techniques using No-Code Platforms
    • Feature Engineering without Coding
    • Dimensionality Reduction
    • Handling Categorical Data
    • Balancing Imbalanced Datasets
    • Advanced Imputation Techniques
    • Advanced Outlier Detection and Treatment
    • Data Warehousing and ETL Processes
  • PG NC - Machine Learning Algorithms
    • Supervised Learning Algorithms
    • Linear Regression and Polynomial Regression
    • Using No-Code Tools for Linear Regression
    • Logistic Regression and Classification Algorithms
    • Decision Trees, Random Forests and K-Nearest Neighbors
    • Building Classifiers using No-Code Tools
    • Unsupervised Learning Algorithms
    • Clustering Techniques
    • No-Code Clustering Tools and Visualizations
    • Dimensionality Reduction Techniques using No-Code Tools
    • Anomaly Detection and Outlier Analysis
    • Evaluation Metrics for Regression
    • Evaluation Metrics for Classification
    • No-Code Tools for Model Evaluation
  • PG NC - Advanced ML Techniques & NLP
    • Ensemble Learning Methods (e.g., Bagging, Boosting)
    • Support Vector Machines (SVM)
    • Introduction to Artificial Neural Networks
    • Building Blocks and Learning Process of ANNs
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    • Attention Mechanism
    • Building and Training Neural Network Model with No-Code Tools
    • Text Analytics and Natural Language Processing (NLP)
    • Text Processing, Representation, and Sentiment Analysis without Coding
    • Building NLP Models using No-Code Platforms
    • Vector Embeddings
  • PG NC - Model Optimization and Deployment
    • Cross-Validation Techniques (K-fold, Stratified, etc.)
    • Model Selection Strategies (Hyperparameter Tuning, Grid Search, Randomized Search, etc.)
    • Bias-Variance Tradeoff and Overfitting/Underfitting
    • Feature Selection Techniques without Programming
    • Model Interpretability and Explainability
    • Interpreting Model Outputs and Insights
    • Deploying Models without Coding
    • Integration with Web and Mobile Applications using No-Code Platforms
    • Model Monitoring and Management
  • PG NC - Real-world AI Applications and Case Studies
    • Applications of No-Code Machine Learning in Various Industries
    • Case Studies in Finance (Fraud Detection, Credit Scoring)
    • Case Studies in Healthcare (Diagnosis, Treatment Recommendations)
    • Case Studies in Marketing (Customer Churn Prediction, Targeted Advertising)
    • Case Studies on Predictive Analytics
    • Case Studies on Image Recognition
    • Common Challenges of No-Code ML
    • Best Practices for ML Project Success
    • Ethical Considerations in No-Code ML Deployment
Electives:

Contact Us

1-844-532-7688

( Toll Free )

18+ Skills Covered

  • Data Collection and Acquisition
  • Data Cleaning and Preparation
  • Exploratory Data Analysis EDA
  • Data Transformation Techniques
  • Data Integration Techniques
  • Supervised Learning Algorithms
  • Unsupervised Learning Algorithms
  • Techniques for Model Evaluation
  • Ensemble Learning Methods
  • Support Vector Machines
  • Artificial Neural Networks
  • Text Analytics
  • Natural Language Processing
  • Model Performance Optimization
  • Feature Selection
  • Model Interpretability
  • Generative AI
  • Prompt Engineering

6+ Tools Covered

Amazon SageMaker Canvas LatestDataiku-LatestData RobotKNIMEVertexAI-LatestRapidMinder-Latest

Industry Projects

  • Project 1

    Comprehensive Data Exploration and Analysis

    Explore a sales dataset with Amazon SageMaker Canvas, clean and analyze data, apply visualization and statistical techniques, and enhance your analytical skills.

  • Project 2

    Predicting Advertising Revenue

    Create a predictive model to forecast TV ad revenue, improving revenue predictions based on promotional spending and optimizing marketing resource allocation for higher returns.

  • Project 3

    Customer Churn Prediction

    Build an SVM model to predict customer churn for a telecom company, improving retention strategies by analyzing demographics and usage patterns to reduce revenue loss.

  • Project 4

    Enhancing Social Media Sentiment Analysis

    Enhance sentiment analysis accuracy on social media data through text preprocessing: normalization, stemming, stop word removal, and tokenization for better insights.

  • Project 5

    Analyzing Machine Failures

    Use Amazon SageMaker Canvas for data analysis and visualization. Create data flows, analyze results, and uncover patterns in machine failure to gain valuable insights.

  • Project 6

    Predicting Car Selling Prices

    Use DataRobot to develop and evaluate a linear regression model for predicting car prices. Analyze relationships like model, mileage, and age for accurate price predictions.

  • Project 7

    Enhancing Sales Data Quality and Analysis

    Enhance data quality with Amazon SageMaker Canvas: create data flows, filter data, handle missing values, perform feature engineering, manage outliers, and validate quality.

  • Project 8

    Detecting Anomalies in Mall Customer Data

    Use DataRobot to detect and resolve anomalies in mall customer data. Load, configure detection, identify, and fix anomalies to enhance data quality for better analysis.

Disclaimer - The projects have been built leveraging real publicly available datasets from organizations.

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Program Advisors

  • Armando Galeana

    Armando Galeana

    Founder and CEO at Ubhuru Technologies

    A seasoned data science leader, with extensive experience in digital transformation. Throughout his career, Armando has leveraged his vast expertise in AI & ML to build infrastructure, create new lines of business and drive global implementations.

  • Arijit Mitra

    Arijit Mitra

    Director and Head of Machine Learning & AI at Pegasystems

    Arijit is an engineering & product leader with expertise in building and deploying AI, NLP, GPT & LLMs at scale for Fortune 500 companies. As head of AI & ML at Pega, he owns the overall AI roadmap with a focus on AI applications across functions.

  • Amitendra Srivastava

    Amitendra Srivastava

    Chief Data Scientist at Intelytica

    Amitendra’s expertise lies in utilizing data analysis and machine learning techniques to solve complex business problems and drive strategic decisions. As Chief Data Scientist, he leverages the power of data to create value and drive innovation.

  • Ankit Virmani

    Ankit Virmani

    Data & ML Leader at Google

    Ankit is an ethical AI and data engineering enthusiast with 10+ years of experience at firms like Google, Amazon, and Deloitte. He serves as a member of the Forbes Technology Council, IU's Institute of Business Analytics, and AI 2030.

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Career Support

Simplilearn Career Assistance

Simplilearn’s Career Assist program, offered in partnership with Talent Inc, is a service to help you to be career ready for the workforce and land your dream job in U.S. markets.
One-on-one Interview Service by TopInterview

One-on-one Interview Service by TopInterview

Get a Resume Makeover from TopResume

Get a Resume Makeover from TopResume

Reach numerous employers with ResumeRabbit

Reach numerous employers with ResumeRabbit

Complete Candidate Confidentiality Assured

Complete Candidate Confidentiality Assured

Industry Trends

No-code AI & machine learning platforms are transforming businesses by democratizing AI capabilities. User-friendly interfaces enable individuals without coding skills to create AI applications, eliminating traditional complexities and enabling broader AI adoption.

Job Icon$225.91 bn

Expected global Machine Learning (ML) market size by 2030

Source: Fortune Business
Job Icon28.3%

The global no-code AI platform market’s projected CAGR from 2023-2033

Source: Future Market
Job Icon20 mn to 50 mn

Potential new jobs expected to be created by AI by 2030

Source: McKinsey & Co

Batch Profile

This No-code AI & Machine Learning program caters to working professionals across different industries. Learner diversity adds richness to class discussions and interactions.

  • Industry
    The class consists of learners from excellent organizations and diverse industries
    Industry Profile
    Information Technology - 43%Software Product - 13%Manufacturing - 20%Phrama & Healthcare - 7%BFSI - 7%Others - 10%
    Companies
    Google
    Microsoft
    Amazon
    IBM
    OpenAI
    Adobe
    Apple
    Intel
    Accenture
    Capegemini

Admission Details

Application Process

The application process consists of three simple steps. An offer of admission will be made to the selected candidates and can be accepted by them by paying the admission fee.

STEP 1

Submit Application

Briefly outline your education and professional experience.

STEP 2

Reserve Your Seat

Complete your payment to reserve your admission.

STEP 3

Start Learning

Selected candidates can begin the program within 1-2 weeks

Eligibility Criteria

For admission to this No Code AI & Machine Learning program, candidates should:

Be at least 18 years old and have a high school diploma or equivalent
Can be from a programming or non-programming background
Preferably have 2+ years of professional work experience

Admission Fee & Financing

The admission fee for this program is $ 2,565.

Financing Options

We are dedicated to making our programs accessible. We are committed to helping you find a way to budget for this program and offer a variety of financing options to make it more economical.

Total Program Fee

$ 2,565

Pay In Installments, as low as

$ 257/month

You can pay monthly installments for Post Graduate Programs using Splitit, ClimbCredit or Klarna payment option with low APR and no hidden fees.

Apply Now

Program Benefits

  • Certificate from Purdue University Online and Simplilearn
  • Live online masterclasses by Purdue faculty and staff
  • Access to Purdue’s alumni association membership
  • 50+ hours of curriculum delivered in live online classes
  • Exposure to DataRobot, Dataiku, KNIME, and other tools

Program Cohorts

Next Cohort

Got questions regarding upcoming cohort dates?

No Code AI & Machine Learning Course FAQs

  • What is a No code AI and machine learning program?

    Simplilearn's no code AI and machine learning program is designed for professionals who want to implement AI and machine learning solutions without coding. The course teaches participants how to use no-code platforms to build, train, and deploy AI models. It covers fundamental AI concepts, practical applications, and project implementation using user-friendly tools. Ideal for business professionals and analysts, this program enables users to integrate AI into their work efficiently and effectively.

  • What does a machine learning engineer do?

    A machine learning engineer designs and builds systems that use data to make predictions or automate tasks. They are also adept in creating and training machine learning models, fine-tuning algorithms, and optimizing systems for performance and scalability. They work with large datasets, code in languages like Python, and collaborate with data scientists and software engineers to deploy models in real-world applications.

  • What are the benefits of a no code AI and machine learning program?

    A nocode AI and ML program offers accessibility for those without a technical background, helping people to leverage AI tools effectively. With  Simplilearn’s no code AI and machine learning program, learners learn the development process by prototyping and deploying machine learning models without extensive coding. After completing it, you will learn to reduce the cost and complexity of AI projects to make AI technologies more affordable for businesses and individuals.

  • How efficient are the trainers at Simplilearn?

    Trainers for Simplilearn's no code AI and machine learning course have extensive experience in the AI industry. They are experts who have created and implemented AI and ML strategies for various industries. Their selection process involves carefully evaluating their educational background, professional experience, and teaching capabilities. Trainers in these courses know GenAI tools, methodologies, and frameworks well enough to explain complicated concepts in an easy-to-understand manner. The instructors' real-world experiences and insights facilitate a highly relevant learning experience.

  • How do I enroll in the no code machine learning course?

    The application process for the No code machine learning program involves three steps. 

    • First, candidates must submit an application detailing their motivation for the course. 

    • Next, an admission panel will review the applications and shortlist candidates based on their submissions. 

    • Finally, selected candidates can begin the course within 1-2 weeks. 

    Please note that, upon selection, candidates must pay the course fee using any preferred payment option available before beginning their learning journey.

  • What will be the career path after completing the no code ai and machine learning Program?

    After completing the no code AI and machine learning program, you can pursue roles like AI specialist, data analyst, or machine learning technician. There is high demand for AI and ML experts in industries like healthcare, finance, or marketing, which leverage AI tools without needing extensive coding skills. The program can also pave the way for automation, product management, or AI consulting roles, allowing you to implement and manage AI-driven solutions across various sectors.

  • What is covered under the 24/7 Support promise?

    We offer 24/7 support through chat for any urgent issues. For other queries, we have a dedicated team that offers email assistance and on-request callbacks.

  • What is the refund policy for this no code machine learning course?

    You can cancel your enrollment if necessary. We will refund the course price after deducting an administration fee. To learn more, please read our refund policy.

  • Does Simplilearn have Corporate Training solutions?

    Simplilearn for Business works with Fortune 500 and mid-sized companies to provide their workforce with digital skills solutions for talent development. We offer diverse corporate training solutions, from short skill-based certification training to role-based learning paths. We also offer Simplilearn Learning Hub+ - a learning library with unlimited live and interactive solutions for the entire organization. Our curriculum consultants work with each client to select and deploy the learning solutions that best meet their teams’ needs and objectives.

  • Will missing a live class affect my ability to complete the course?

    No, missing a live class will not affect your ability to complete the course. With our 'flexi-learn' feature, you can watch the recorded session of any missed class at your convenience. This allows you to stay up-to-date with the course content and meet the necessary requirements to progress and earn your certificate. Simply visit the Simplilearn learning platform, select the missed class, and watch the recording to have your attendance marked.

  • Are Simplilearn’s courses eligible for reimbursement by my employer?

    Yes, Simplilearn’s No Code AI and Machine Learning Specialization, offered in collaboration with Purdue University, is eligible for employer reimbursement. We'd recommend confirming the specific terms of educational benefits or tuition assistance programs with your HR department or employer. Purdue also accepts tuition vouchers, which can streamline reimbursement.

    To claim your reimbursement, Simplilearn offers completion certificates, detailed receipts, and course breakdowns, which can be submitted to your employer or HR department.

  • Are there any other online courses Simplilearn offers under AI & Machine Learning?

    Absolutely! Simplilearn offers plenty of options to help you upskill in AI & Machine Learning. You can take advanced certification training courses or niche courses to sharpen specific skills. Whether you want to master new tools or stay ahead with the latest trends, there's something for everyone. These courses are designed to elevate your knowledge and keep you competitive in the AI & Machine Learning field.

    Similar programs that we offer under AI & Machine Learning

  • Can you learn AI and ML without coding?

    Yes, you can learn AI and machine learning without coding, thanks to nocode platforms that offer user-friendly tools to build and deploy models. Simplilearn’s no code AI and machine learning course allows you to work with pre-built algorithms and drag-and-drop interfaces. It is best suited for non-programmers who want to understand and apply AI concepts. However, having a grasp of basic data concepts and AI principles will enhance your ability to effectively use these tools.

  • Is machine learning a promising career?

    Yes, machine learning can be a highly rewarding career. The demand for ML experts is constantly growing across industries like finance, healthcare, and tech. The rise of AI-driven technologies has made machine learning experts highly sought after for their ability to create predictive models, automate processes, and drive innovation. The field offers competitive salaries, diverse job opportunities, and the chance to work on cutting-edge solutions, making it a promising and future-proof career choice.

  • What is the future of nocode machine learning?

    The future of nocode machine learning is bright. The field democratizes AI by allowing non-technical users to build and deploy machine learning models without coding. This trend will boost and accelerate innovation across industries, helping businesses to harness the power of AI. With user-friendly interfaces and pre-built algorithms, no-code AI platforms will empower more professionals to integrate AI into their workflows. The AI tools will proceed to bridge the gap between technical and non-technical teams and make AI more accessible to everyone.

  • Which companies hire machine learning engineers?

    Many top global companies hire ML engineers. This includes tech giants like Google, Amazon, and Microsoft, which use AI for search engines, cloud services, and automation. Other companies in industries like finance (JPMorgan Chase), healthcare (Pfizer, Medtronic), and automotive (Tesla, Waymo) also seek ML engineers to drive innovation. In addition, many startups, research labs, and companies such as OpensAI and Nvidia also frequently hire machine learning professionals to build AI products and solutions.

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