Caltech Post Graduate Program in Data Science
Caltech is Ranked #4 in Best Universities in the US by Times Higher Education
Advance your data science career with this PG in Data Science, collaborating with Caltech CTME and IBM. This program teaches you skills and tools including ML, Python, Tableau, generative AI, explainable AI, ChatGPT, and more. The program also includes masterclasses by Caltech faculty & IBM experts.
- Learning Format Self-Paced Learning
World’s #1 Online Bootcamp
Why Join this Program
Fast-track Your Career
Simplilearn’s Career Assistance service has demonstrated strong performance by means of average salaries offered, the number of hiring companies participating, and the pace of job offer roll-outs.
Our Placement Stats
Maximum salary hike
150%Average salary hike
70%Hiring partners
2900+Our Alumni In Top Companies
Program Overview
This Caltech Post Graduate Program in Data Science leverages the superiority of Caltech's academic eminence covering critical data science topics like Python, R, machine learning, data visualization tools, generative AI, explainable AI, ChatGPT, and more through an interactive learning model with live sessions led by global practitioners.
Key Features
- Earn a program certificate and up to 14 CEUs from Caltech CTME
- Generative AI and prompt engineering: Explore a dedicated course with live sessions
- Learn about ChatGPT, DALL-E, Midjourney & other prominent tools
- Caltech CTME Circle Membership and online convocation by Caltech CTME Program Director
Post Graduate Program Advantage
This Data Science Post Graduate Program leverages Caltech's academic prowess and helps you pursue a successful career in data science.
Partnering with Caltech CTME
- Masterclasses delivered by distinguished Caltech CTME instructors
- Program completion certificate from Caltech CTME
- Earn up to 14 CEUs to showcase your achievements
Program in Collaboration with IBM
- Industry-certified IBM certificates for IBM courses
- Industry masterclasses delivered by IBM
- Hackathons from IBM
Program Details
Embark on a meticulously crafted learning journey in generative AI, explainable AI, prompt engineering, ChatGPT, statistics, Python, data analysis, machine learning, data visualization, and more. Elevate your data science expertise and advance your career.
Learning Path
Welcome to this PG in Data Science, developed and presented with Caltech CTME and IBM, which will help you become an expert in the data science domain.
- Develop a comprehensive understanding of coordinate geometry and linear algebra.
- Comprehend the concepts of eigenvalues, eigenvectors, and eigendecomposition.
- Build a strong foundation in calculus, including limits, derivatives, and integrals.
- Distinguish between various types of statistics and recognize their applications
- Comprehend the differences between structured and unstructured data.
- Describe mean absolute deviation (MAD), standard deviation, and variance.
- Analyze the outcomes of hypothesis testing, including one-tail and two-tail test
- Acquire proficiency in both procedural and object-oriented programming.
- Recognize the advantages and benefits of using Python as a programming language.
- Install Python and its integrated development environment.
- Familiarize yourself with the Jupyter Notebook and its practical applications.
- Implement Python identifiers, indentations, and comments effectively.
- Understand Python's data types, operators, and string functions.
- Learn about the various types of loops in Python.
- Describe methods, attributes, and access modifiers in Python.
- Attain a thorough grasp of databases and their interconnections.
- Gain proficiency in utilizing popular query tools and handling SQL commands.
- Achieve mastery in managing databases efficiently, covering transactions, table creation, and utilizing views.
- Comprehend and successfully execute stored procedures for the execution of complex operations.
- Explore a range of SQL functions, including those related to strings, mathematics, date and time, and pattern matching.
- Grasp the functions related to user access control to ensure the security of databases.
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Craft your inaugural Python script incorporating variables, strings, functions, loops, and conditional statements.
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Gain a firm grasp of Python's fundamental principles, including lists, sets, dictionaries, conditional logic, branching, object-oriented programming, and classes.
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Harness the power of the Pandas library to import, manipulate, save data, and manage file operations in Python.
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- Delve into the phases of data preparation, model construction, and assessment.
- Develop a solid grasp of NumPy and its practical applications, encompassing array indexing and slicing techniques.
- Elaborate on the null hypothesis and the alternative hypothesis within the context of hypothesis testing.
- Examine various hypothesis tests, including the Z-test, T-test, and ANOVA.
- Engage with pandas' core data structures, namely Series and DataFrame.
- Leverage pandas for tasks.
- Generate compelling visualizations using libraries like Matplotlib, Seaborn, Plotly, and Bokeh.
- Scrutinize the machine learning pipeline and attain a thorough comprehension of the essential processes integral to machine learning operations
- Investigate both supervised and unsupervised learning techniques.
- Detect and generate correlation maps to explore the relationships between variables.
- Enumerate various types of classification algorithms and grasp their specific practical applications.
- Explore assorted ensemble modeling methods, such as bagging, boosting, and stacking.
- Construct a recommendation system utilizing PyTorch.
- Attain mastery in a range of visualization techniques,
- Demonstrate adeptness in strategically using filters, parameters, and sets for effective data manipulation.
- Become skilled in the utilization of special field types and Tableau-generated fields.
- Acquire the knowledge and skills to craft diverse charts, interactive dashboards, and engaging story interfaces.
- Develop proficiency in data blending, the creation of data extracts, and the efficient organization and formatting of data.
The Data Science Capstone project provides a valuable opportunity to apply the skills you have acquired during this Program. With the guidance of dedicated mentors, you will address a real-world data science problem aligned with industry standards. This comprehensive project covers data processing, model building, and reporting business results and insights. It is the final step in your learning journey and enables you to demonstrate your data science expertise to potential employers.
Electives:
- Acquire an understanding of mathematical concepts, variables, strings, vectors, factors, and operations involving vectors.
- Develop a foundational grasp of arrays, matrices, lists, and data frames in R.
- Gain insight into topics including conditions, loops, functions, objects, classes, and debugging within the R environment.
- Learn how to effectively import and manipulate text, CSV, and Excel files, as well as write and store data objects in R.
- Comprehend the manipulation of strings and date-related operations in R.
Attend an online interactive masterclass and get insights about advancements in technology/techniques in Data Science by Caltech
Attend this online interactive industry master class to gain insights about Data Science advancements
- Comprehend the significance of business analytics and its role in the industry.
- Gain a foundational understanding of Excel analytics functions and the utilization of conditional formatting.
- Acquire the skills to analyze intricate data sets using pivot tables and slicers.
- Apply statistical methodologies and principles, including moving averages, hypothesis testing, ANOVA, and regression, to data sets within Excel.
- Depict your insights and results through the creation of charts and dashboards.
- Acquire the knowledge and techniques to scrutinize data and derive valuable insights
- Craft interactive dashboards that facilitate data visualization
- Enhance overall operational efficiency and effectiveness within your organization.
- Learn the art of crafting dashboards from existing published reports.
- Explore the utilization of Quick Insights to uncover valuable data patterns swiftly.
- Acquire valuable troubleshooting techniques to address potential issues effectively.
- Establish a foundational understanding of artificial intelligence and generative AI models.
- Grasp the concept of explainable AI.
- Implement effective prompt engineering methods to enhance performance.
- Recognize and explore various applications and practical scenarios where ChatGPT can be employed.
- Familiarize yourself with fine-tuning techniques to tailor and optimize ChatGPT models
- Acknowledge the ethical dilemmas associated with generative AI models and ChatGPT.
- Gain a perspective on the future of generative AI, including the challenges it may face as it evolves.
Program Advisors
Rick Hefner
Caltech CTME, Program DirectorDr. Rick Hefner serves as the Program Director for Caltech’s CTME, where he develops customized training programs for technology-driven organizations. He has over 40 years of experience in systems development and has served in academic, industrial, and research positions.
Join the Data Science industry
Data Science and Artificial Intelligence are amongst the hottest fields of the 21st century that will impact all segments of daily life by 2025, from transport and logistics to healthcare and customer service.
28%Annual Job Growth By 2026
11.5 MExpected New Jobs For Data Science By 2026
$86K - $157KAverage Annual Salary
Companies Hire Data Scientists
Batch Profile
This Data Science program caters to working professionals across industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.
- The class consists of learners from excellent organizations and diverse industriesIndustryInformation Technology - 41%Consulting - 20%Pharma & Healthcare - 8%Manufacturing - 8%BFSI - 8%Others - 15%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 accepted by the candidates 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 Post Graduation in Data Science, candidates should have:
Apply Now
Program Benefits
- Program certificate & up to 14 CEUs from Caltech CTME
- Exposure to ChatGPT, generative AI, Explainable AI and more
- Masterclasses led by distinguished Caltech instructors
- Gain access to Caltech CTME Circle Membership
- Simplilearn’s Career Assistance post-program completion
FAQs
What are the key learning outcomes of the course “Essentials of Generative AI, Prompt Engineering and ChatGPT”?
This course will give you a holistic understanding of the essentials of generative AI and its landscape, prompt engineering, explainable AI, conversational AI, ChatGPT and other LLMs.
The key learning objectives of this course are:
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Understand the fundamentals of generative AI models, including the working principles and various generative AI models.
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Comprehend the concept of explainable AI, recognize its significance and identify different approaches to achieve explainability in AI systems.
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Apply effective prompt engineering techniques to improve the performance and control the behavior of generative AI models.
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Understand ChatGPT, including its working mechanisms, notable features and limitations.
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Identify and explore diverse applications and use cases where ChatGPT can be leveraged.
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Gain exposure to fine-tuning techniques to customize and optimize ChatGPT models
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Recognize the ethical challenges of generative AI models and ChatGPT to ensure responsible data usage, mitigate bias and prevent misuse.
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Understand the potential of generative AI to revolutionize industries and explore prominent generative AI tools.
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Gain insights into the future of generative AI, its challenges and the steps needed to unlock its full potential.
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What are the key topics covered in the course “Essentials of Generative AI, Prompt Engineering and ChatGPT”?
Some of the key topics covered in the course “Essentials of Generative AI, Prompt Engineering and ChatGPT” are:
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Generative AI and its Landscape
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Explainable AI
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Conversational AI
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Prompt Engineering
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Designing and Generating Effective Prompts
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Large Language Models
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ChatGPT and its Applications
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Fine-tuning ChatGPT
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Ethical Considerations in Generative AI Models
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Responsible Data Usage and Privacy
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The Future of Generative AI
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AI Technologies for Innovation
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What is Data Science?
Data science is the domain that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions.
What are the top Data Science courses included in this program?
This Data science program gives you a step-by-step guide to learning all the concepts from scratch. The entire syllabus is divided into the following courses:
- R Programming for Data Science
- Data Science with R
- Python for Data Science
- Data Science with Python
- Machine Learning
- Natural Language Processing
- Tableau Training
- Data Science Capstone
- Disclaimer
- PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.