Why Learn No Code AI & Machine Learning Skills
Don't let coding barriers hold you back from the AI revolution. The demand for artificial intelligence and machine learning professionals is slated to increase about 36% over the next decade (U.S. Bureau of Labor Statistics).
For roles like Machine Learning Engineer and AI Research Scientist, the average salary exceeds $125,000 annually (ZipRecruiter). By using simple drag-and-drop tools, anyone can apply AI solutions without knowing complex coding. From optimizing marketing campaigns and improving customer experiences to predicting market trends and automating processes, the applications of no-code AI and machine learning are vast.
Gaining no-code AI and machine learning skills can boost organizational efficiency, unlock new career opportunities, and stimulate the innovation needed for business growth. Apply now to the No Code AI & Machine Learning Specialization course to take the next step toward getting these in-demand skills.
No Code AI & Machine Learning Specialization Course Benefits
Unlock the potential of AI and machine learning no-code platforms with this dynamic course delivered by Simplilearn and Purdue University Online. You’ll learn to seamlessly perform data analysis, create robust models, and make data-driven decisions with confidence.
You’ll also dive into hands-on learning using intuitive AI and machine learning no-code platforms that allow you to drag-and-drop interfaces, harness the power of automated machine learning, and navigate through visual workflows with ease.
Here’s what you’ll benefit from in the No Code AI & Machine Learning Specialization course:
Partnership with Simplilearn & Purdue University Online
The program awards you a joint certificate from Simplilearn and Purdue University Online. Additionally, you'll gain access to Purdue's alumni network, a valuable resource for potential career opportunities.
Gain Knowledge From Experts
Learn live online in 50+ hours of course material delivered by industry-experienced practitioners. Plus, get access to a masterclass taught by Purdue faculty and staff.
Experiential Learning Through Practical Application
Use DataRobot, Dataiku, Amazon SageMaker Canvas, and other in-demand tools to solve real-world problems in hands-on projects.
Receive Career Assistance
Make your resume stand out and showcase your newly acquired skills to employers with career assistance services from Simplilearn.
Course Schedule
The No-Code AI & Machine Learning Specialization offers a flexible online format and convenient schedules that allow you to balance career development with your other commitments.
Upcoming Dates
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Monday, Wednesday, & Thursday
7:30 PM to 10:30 PM ET
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Saturday & Sunday
9:30 AM-12:30 AM ET
Class time options vary by month and are subject to change. To see available class times for your cohort of choice, complete your application or schedule a call with a student advisor.
Tuition & Payment Plans
Purdue University Online is committed to making tech education more accessible, which is why we accept a variety of payment options to help make tuition more economical.
Tuition: $2,565
Pay tuition in full or through a payment plan for as low as $237/ month.
Get a Tuition Credit for a Limited-Time: Enroll in and complete the No-Code AI & Machine Learning Specialization course and receive a $2,565 tuition credit towards a Fullstack Academy bootcamp.
Stack Your Benefits: Combine this credit with select Fullstack Academy scholarships to further reduce the cost of your bootcamp.
About Simplilearn & Purdue University Online
Purdue University is a top public research institution developing practical solutions to today’s toughest challenges. Ranked in each of the last six years as one of the 10 Most Innovative Universities in the United States by U.S. News & World Report (2024), Purdue delivers world-changing research and discovery.
Simplilearn delivers various online professional programs with academic institutions including Purdue University Online. Simplilearn’s award-winning immersive learning model focuses on applied learning experiences intended to create immediate impact.
No Code AI & Machine Learning Course Curriculum
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Get started with the No Code AI and Machine Learning Specialization, delivered by Simplilearn and Purdue University Online. Kickstart your learning journey and explore the ability to build practical AI solutions using no-code tools.
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Overview of AI, Machine Learning, and Their Importance
Machine Learning Life Cycle
Machine Learning Challenges
Introduction to Machine Learning Operations
Introduction to No-Code AI & Machine Learning
Advantages and Limitations of No-Code AI & Machine Learning
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
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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 Extract, Transform, and Load Processes
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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
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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
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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
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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 Machine Learning
Best Practices for Machine Learning Project Success
Ethical Considerations in No-Code Machine Learning Deployment
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Academic Masterclass by Purdue University
Attend an online interactive masterclass and get insights about advancements in technology and techniques in no-code machine learning
Essentials of Generative AI, Prompt Engineering, & ChatGPT
Learn generative AI, prompt engineering, and ChatGPT
Acquire a real-world understanding of business applications
Master the art of applying generative AI efficiently
Grasp the significance of prompt engineering by producing tailored outputs
Please note that this is a sample curriculum and is subject to change.
No Code AI & Machine Learning Tools
Sample Curriculum Projects
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Explore a sales dataset with Amazon SageMaker Canvas, clean and analyze data, apply visualization and statistical techniques, and enhance your analytical skills.
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Create a predictive model to forecast TV ad revenue, improving revenue predictions based on promotional spending and optimizing marketing resource allocation for higher returns.
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Build a support vector machine (SVM) model to predict customer churn for a telecom company, improving retention strategies by analyzing demographics and usage patterns to reduce revenue loss.
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Enhance sentiment analysis accuracy on social media data through text preprocessing: normalization, stemming, stop word removal, and tokenization for better insights.
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Use Amazon SageMaker Canvas for data analysis and visualization. Create data flows, analyze results, and uncover patterns in industrial machine failure to gain valuable insights.
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Use DataRobot to develop and evaluate a linear regression model for predicting vehicle prices. Analyze relationships like model, mileage, and age for accurate price predictions.
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Enhance data quality with Amazon SageMaker Canvas: create data flows, filter data, handle missing values, perform feature engineering, manage outliers, and validate quality.
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Use DataRobot to detect and resolve anomalies in retail customer data. Load, configure detection, identify, and fix anomalies to enhance data quality for better analysis.
Curriculum Advisors
Founder and CEO at Ubhuru Technologies
Armando is a seasoned leader in data science with extensive experience in digital transformation. Throughout his career, Armando has leveraged his vast expertise in AI and machine learning to build infrastructures, create new lines of business, and drive global implementations.
Director and Head of Machine Learning & AI at Pegasystems
Arijit is an engineering and product leader with extensive knowledge in building and deploying AI, natural language processing, generative pre-trained transformers, and large language models at scale for Fortune 500 companies. As head of AI and machine learning at Pegasystems, he owns the overall AI roadmap focusing on applications across functions.
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.
Data & Machine Learning 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.
Career Opportunities
AI is reshaping industries, but the complexity of its underlying technologies often creates a barrier to entry. AI and machine learning no-code platforms offer a game-changing solution. Here are a few job titles for this evolving field:
Builds and deploys machine learning models into production systems.
Extracts insights from data to solve complex problems using statistical and machine learning techniques.
Conducts research to advance the field of artificial intelligence by developing new algorithms and models.
Companies Hiring
No Code AI & Machine Learning Specialization Course Outcomes
The No Code AI & Machine Learning Specialization course gives you the skills to quickly build AI solutions and make data-driven decisions—all without coding expertise.
Learn by doing: Apply what you learn to real-world problems.
Purdue-backed: Get a certificate of completion jointly issued by Simplilearn & Purdue University Online.
Expert teaching: Masterclasses led by Purdue University faculty and staff.
Eligibility Requirements
For the No Code AI and Machine Learning Specialization, prior technical or programming experience is not necessary to apply or be accepted into the course.
Required for Admission:
Be at least 18 years old
Have a high school diploma or equivalent
Preferred Qualifications:
Preferably have 2+ years of professional work experience, but not mandatory
Who Should Attend the No Code AI & Machine Learning Course
The No Code AI and Machine Learning Specialization is ideal for recent grads and current professionals looking to upskill or reinforce their existing expertise.
Professionals who benefit from this course may include:
AI Enthusiasts
Business Leaders
Consultants
Data Professionals
Entrepreneurs
IT Professionals
Product Managers
Program Managers
Admissions Process
Ready to get started?
Apply to the No Code AI & Machine Learning Specialization course! Here’s how:
- Fill out our online application form
- Take our nontechnical assessment
- Covers logical reasoning
- Sent to you immediately upon submission of the application
- Receive an entrance decision
No Code AI & Machine Learning Course FAQs
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The No Code AI and Machine Learning Specialization will take 16 weeks to complete.
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The curriculum for the No Code AI and Machine Learning Specialization is taught by professionals who bring industry insights and practical experience to the classroom. These industry professionals are selected after a thorough evaluation of their technical and pedagogical skills.
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Once you successfully complete the No Code AI & Machine Learning course, you’ll receive a certificate of completion jointly issued by Simplilearn and Purdue University Online.
