• Program Duration16 weeks
  • Learning FormatOnline Bootcamp
  • Admission closes on
    Jun 19th, 2024

Program Highlights

  • Partnership with Purdue University Online

    Joint program certificate from Purdue University Online and Simplilearn

    Become eligible for a membership at the Purdue University Alumni Association

  • Learn from the Experts

    50+ hours of core curriculum delivered in live online classes by industry experts

    Live online masterclasses delivered by Purdue faculty and staff

  • Experiential Learning through Practical Application

    Exposure to DataRobot, Dataiku, Amazon SageMaker Canvas, and other tools

    Apply your knowledge through hands-on projects spanning various industries

  • Simplilearn Career Service

    Strengthen your resume and get career guidance from industry specialists

    Attend mock interview sessions to help you ace the hard technical questions



Career Opportunities

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Program Outcomes

Program CertificateProgram Certificate
  • Program certificate from Purdue University Online and Simplilearn
  • Become eligible for a membership at the Purdue Alumni Association
  • Exposure to Amazon SageMaker Canvas, DataRobot, and other tools
  • Implement no-code ML in real-world scenarios through hands-on projects

Program Curriculum

  • Get started with the Professional Certificate Program in No Code Machine Learning, 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.

  • Discover the power of machine learning with this introductory course on its fundamentals. Learn about the different types of machine learning algorithms, the machine learning life cycle, and the challenges that come with it. Get introduced to no-code machine learning tools and platforms, and understand the importance of MLOps in scaling machine learning models. Gain knowledge to apply machine learning techniques to real-world problems and learn when to use no-code tools versus when to code.

  • Gain hands-on experience in collecting, cleaning, and preparing data for analysis. Learn about various data sources, data formats, and data acquisition techniques. Explore no-code platforms for data collection, import, and preprocessing, and discover advanced techniques for data cleaning and exploratory data analysis. Gain expertise in handling missing values, outliers, categorical data, text data preprocessing, and advanced feature engineering.

  • This course on Machine Learning Algorithms offers a comprehensive grasp of supervised and unsupervised learning. Covers linear and polynomial regression, logistic regression, classification algorithms, clustering techniques, dimensionality reduction techniques, and anomaly detection. The course emphasizes the use of no-code tools for building models, clustering, dimensionality reduction, and anomaly detection, making it accessible and practical for learners of all backgrounds.

  • Explore advanced topics in machine learning, including ensemble learning methods such as Bagging, Boosting, and Gradient Boosting Machines like XGBoost and LightGBM. It also explores Support Vector Machines (SVM) for classification and regression and introduces neural networks, including artificial neural networks (ANNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) networks.

  • Learn model performance optimization, feature selection, model interpretability, and model deployment using no-code tools. The course provides hands-on projects and real-world case studies and covers tools such as DataRobot AI, KNIME, and Dataiku, which enable users to classify information, perform data analysis, and create accurate data predictions with models.

  • Explore real-world applications and case studies of no-code machine learning in various industries, including finance, healthcare, and marketing. Learn from case studies on predictive analytics, image recognition, and more. Discover best practices, lessons learned, and ethical considerations in no-code machine learning deployment. Unlock the power of no-code AI and machine learning tools to make data-driven business decisions and build intelligent solutions without writing code.

Skills Covered

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

Tools Covered

Amazon SageMaker Canvas Latest
Data Robot

Program Advisor

Total Program Fee

Program Fee $ 2,565

Pay in Installments

As low as

You can pay monthly installments using Splitit, Climb Credit and Klarna.These plans are offered with low APR and no hidden fees.

Eligibility Criteria

  • At least 18 years with a high school diploma or equivalent
  • Can be from a programming or non-programming background
  • Preferably have 2+ years of professional work experience

Best Suited For

  • AI Enthusiasts
  • Data Professionals
  • IT Professionals
  • Business Professionals
  • Product Managers
  • Consultants

How to Apply

  • STEP 1Submit Application

    Tell us a bit about yourself and why you want to do this program

  • STEP 2Application Review

    An admission panel will shortlist candidates based on their application

  • STEP 3Admission

    Selected candidates can begin the program within 1-2 weeks

Apply Now

Demand for Program

The no-code AI platform market, valued at $3.83 billion in 2023, is projected to grow at a 30.6% CAGR from 2024 to 2030. These platforms enable non-programmers and AI experts to implement AI projects, with a growing number of enterprises worldwide driving market growth. No-code AI tools bridge the gap between domain experts and AI specialists, enabling better communication and testing of ideas. The rapid evolution and deployment of AI and machine learning, along with the adoption of IoT, edge computing, and data science solutions, contribute to this market growth. No-code AI platforms allow for the development of AI models without AI professionals, decreasing time and lowering entry barriers for individuals and enterprises to experiment with AI and machine learning. These solutions enable businesses to affordably implement AI models, allowing their domain experts to benefit from cutting-edge technology.

Program FAQs

  • How long does it take to complete the Professional Certificate Program in No Code Machine Learning?

  • Who will be the faculty for the Professional Certificate Program in No Code Machine Learning?

  • What certificate will I receive after completing the No Code Machine Learning program?

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