No Code AI and Machine Learning Specialization
Build practical AI solutions using no code tools
Explore our cutting-edge No Code AI & Machine Learning program, a collaboration between Purdue University Online and Simplilearn. Empower yourself to create and deploy machine learning models without writing a single line of code.
- Admission closes on 5 Aug, 2024
- Program Duration 3 months
- Learning Format Online Bootcamp
World’s #1 Online Bootcamp
Why Join this Program
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
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.
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
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.
- 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
- 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
- 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
- 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
- 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
- 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:
Attend an online interactive masterclass and get insights about advancements in technology/techniques in No Code Machine Learning.
- Cutting-edge knowledge: Learn generative AI, prompt engineering, and ChatGPT
- Hands-on skills: Acquire real-world understanding of business applications
- Effective GenAI utilization: Master the art of applying Generative AI efficiently
- Master prompt engineering: Grasp its significance in producing tailored outputs
Program Advisors
Armando Galeana
Founder and CEO at Ubhuru TechnologiesA 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
Director and Head of Machine Learning & AI at PegasystemsArijit 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
Chief Data Scientist at IntelyticaAmitendra’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
Data & ML Leader at GoogleAnkit 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 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
Get a Resume Makeover from TopResume
Reach numerous employers with ResumeRabbit
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.
$225.91 bnExpected global Machine Learning (ML) market size by 2030
28.3%The global no-code AI platform market’s projected CAGR from 2023-2033
20 mn to 50 mnPotential new jobs expected to be created by AI by 2030
Companies Hiring
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.
- The class consists of learners from excellent organizations and diverse industriesIndustry ProfileInformation Technology - 43%Software Product - 13%Manufacturing - 20%Phrama & Healthcare - 7%BFSI - 7%Others - 10%Companies
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.
Submit Application
Tell us a bit about yourself and why you want to do this program
Application Review
An admission panel will shortlist candidates based on their application
Admission
Selected candidates can begin the program within 1-2 weeks
Eligibility Criteria
For admission to this No Code AI & Machine Learning program, candidates should:
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.
Pay in Installments
You can pay monthly installments for Post Graduate Programs using Splitit, ClimbCredit or Klarna payment option with low APR and no hidden fees.
Other Payment Options
We provide the following options for one-time payment
- Credit Card
- Paypal
$ 2,565
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
No Code AI & Machine Learning Course FAQs
How long does it take to complete the No Code AI and Machine Learning Specialization?
The anticipated time to complete the No Code AI and Machine Learning program is 3 to 4 months.
Who will be the faculty for the No Code AI and Machine Learning Specialization?
Industry experts from the data and AI domain lead the curriculum delivery for this No Code AI and ML program, bringing real-world insights and practical knowledge to the classroom. They are selected only after a rigorous shortlisting process, including profile assessment, technical examination, and a training presentation.
The distinguished faculty members from Purdue University deliver the masterclasses for this program.What certificate will I receive after completing the No Code AI and Machine Learning Specialization?
Upon completing this No Code AI and Machine Learning program, you will be awarded a joint certificate of completion from Purdue University Online and Simplilearn.
What are the eligibility requirements for the No Code AI and Machine Learning program?
You must meet the following requirements to join the online No Code AI & ML program:
- Be at least 18 years old and have a high school diploma or equivalent
- Preferably have 2+ years of professional work experience, but not mandatory
- Prior technology know-how or programming experience is not necessary
- Disclaimer
- PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.