The Data Science and Artificial Intelligence Dual Master’s program in collaboration with IBM helps you gain an edge in your career, earn a certification, master the critical skills required in these two growing fields.
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.
for Data Scientists jobs by 2020
(as per IBM)
jobs will be created because of AI By 2020
(as per Gartner)
An estimated 80% of companies are already investing in AI and most are facing challenges hiring the capabilities they need to implement a useful AI application or product.
- Harvard Business ReviewThe January 2019 report from Indeed, one of the top job sites, showed a 30% increase in demand for data scientists year over year and a 348% increase since 2013, a dramatic upswing.
- ForbesIBM is one of the leading innovators in data science and infuses this course with industry relevant, hands-on training.
The Simplilearn Dual Master’s Program enables you to earn industry-recognized certificates for both Data Scientist and Artificial Intelligence Engineer within a single program at an accelerated rate.
Blending extensive hands-on training with self-paced learning co-developed by IBM and instructor-led classes, this Dual Master’s program is designed to make you industry ready. Two capstone projects culminate your learning experience to reinforce your knowledge of Data Science and Artificial Intelligence concepts.
Discover procedural and object-oriented programming. Uncover Python's benefits. Set up Python and its IDE. Master Jupyter Notebook. Apply Python basics like identifiers, indentation, and comments. Understand data types, operators, and string functions. Explore Python loops and variable scopes. Learn about OOP, its features, and elements like methods, attributes, and access modifiers.
* Ideal for aspiring SQL developers and data analysts
* Perfect for enhancing database management skills
* Beginner-friendly course designed by Simplilearn
* Covers basics to advanced topics of SQL
* Learn data storage, retrieval, and manipulation using SQL
Kickstart your learning of Python for Data Science with this Data Scientist course and familiarize yourself with programming, tastefully crafted by IBM.
* Gain a comprehensive overview of Python's tools and techniques for data analytics
* Experience vital skill development in Python for various data science roles
* Engage in a blended learning approach covering data wrangling, mathematical computing, and more
* Explore practical applications for a hands-on understanding
* Propel your data science career with Simplilearn's specialized training
*Gain career success with our comprehensive Machine Learning course
*Learn from 40+ hrs of Applied Learning and interactive labs
*Complete 4 hands-on projects to solidify your understanding
*Receive mentoring support throughout your learning journey
*Master essential machine learning concepts for certification
*Gain the skills needed to become a successful machine learning engineer
This Tableau certification course helps you master Tableau Desktop, a world-wide utilized data visualization, reporting, and business intelligence tool. Advance your career in analytics through our Tableau training and gain job-ready skills. Tableau certification is highly regarded by companies for data-related jobs and our Tableau online course trains you to use the tool effectively for preparing data, creating interactive dashboards, adding different dimensions, and drilling into outliers.
Simplilearn’s Data Science Capstone project will give you an opportunity to implement the skills you learned in the Data Science course. Through dedicated mentoring sessions, you’ll learn how to solve a real-world, industry-aligned Data Science problem, from data processing and model building to reporting your business results and insights. The project is the final step in Data Science training and will help you to show your expertise in Data Science to employers.
Delve into AI basics and generative AI principles. Grasp the importance of explainable AI. Employ prompt engineering to enhance generative AI performance. Understand ChatGPT's mechanisms, features, and constraints. Explore varied ChatGPT applications. Gain foresight into generative AI's future and challenges.
Differentiate deep learning from machine learning. Explore various neural network types. Excel at forward and backward propagation in deep neural networks. Introduce modeling and performance enhancement in deep learning. Understand hyperparameter tuning and model interpretability. Learn dropout and early stopping implementation. Master CNNs, object detection, and RNN fundamentals. Grasp PyTorch basics and neural network creation.
The capstone project allows you to implement the skills you learned throughout this bootcamp. You will solve industry-specific challenges by leveraging various AI and ML techniques. The capstone project will help you showcase your expertise to employers.
Discover R Programming with this introductory course. Learn how to write R code, utilize R data structures, and create your own functions.
Boost your analytics career with powerful new Microsoft® Excel skills by taking this Business Analytics course, which includes training on Power BI. These two commonly used tools, combined with official business analytics certification, will put you on the path of a successful career.
* Aligned with PL-300: Microsoft Power BI Data Analyst certification
* Topics include Power BI Desktop layouts, BI reports, dashboards, DAX commands, and functions
* Learn to experiment, refine, prepare, and present data with ease
* Explore comprehensive Power BI training for hands-on applied learning
* Learn through a practical approach to help you gain expertise
Delve into AI basics and generative AI principles. Grasp the importance of explainable AI. Employ prompt engineering to enhance generative AI performance. Understand ChatGPT's mechanisms, features, and constraints. Explore varied ChatGPT applications. Gain foresight into generative AI's future and challenges.
Attend this online interactive industry master class to gain insights about Data Science advancements and AI techniques.
Enhance ML capabilities with deep learning techniques. Acquire expertise in TensorFlow and Keras. Master deep learning principles. Build artificial neural networks. Explore data abstraction layers. Unleash data's potential for AI progress.
Dive into advanced computer vision and deep learning. Focus on practical skills and deep understanding. Explore image formation, CNNs, and object detection. Learn about image segmentation and generative models. Delve into optical character recognition. Explore distributed and parallel computing. Investigate Explainable AI (XAI). Master deep learning model deployment techniques.
The Natural Language Processing course gives you a detailed look at the science of applying machine learning algorithms to process large amounts of natural language data. NLP is driving the growth of the AI market, and this course helps you develop the skills required to become an NLP Engineer.
Hands - On Reinforcement Learning with Python
Grasp transformers' significance in contemporary AI. Evaluate neural networks' suitability for generative tasks. Differentiate between VAEs, GANs, transformers, and autoencoders. Assess ideal scenarios for each generative model. Evaluate attention mechanisms' efficacy in diverse generative tasks. Analyze GPT and BERT architectural distinctions and objectives in generative AI models.
Attend these online live sessions delivered by industry experts to gain insights about the latest advancements in the AI space. Some of the areas and concepts covered include Generative AI and its Applications, Leveraging the power of generative modeling to build innovative products, Building and deploying GPT-powered applications Demystifying ChatGPT, its architecture, training methodology, and business applications, and Applications of ChatGPT. {*Areas mentioned above are subject to change}
Candidates who wish to apply for this Dual Master’s program in Data Science and Artificial Intelligence should have:
Are you curious to learn Data Science, Machine Learning, and Artificial Intelligence? If yes, then get yourself enrolled today for Simplilearn's Dual Master program and kickstart your career right away!
Not ready to enroll? Watch our free video lessons now.
Simplilearn’s Blended Learning model brings classroom learning experience online with its world-class LMS. It combines instructor-led training, self-paced learning and personalized mentoring to provide an immersive learning experience
As a part of this online training, In collaboration with IBM, you will receive the following:
Data Science is a concept used to tackle Big Data and includes data cleansing, preparation, and analysis. A Data Scientist gathers data from multiple sources and applies machine learning, predictive analytics, and sentiment analysis to extract critical information from the collected data sets. They understand data from a business point of view and are able to provide accurate predictions and insights that can be used to power critical business decisions.
Artificial Intelligence (AI) is an area of computer science that features the creation of intelligent machines that work and react like humans. Some of the activities computers with Artificial Intelligence are designed for speech recognition, computer vision etc.
Machine Learning can be defined as the practice of using algorithms to use data, learn from it and then forecast future trends for that topic. A good example of Machine Learning implementation is Facebook. Facebook’s Machine Learning algorithms gather behavioral information for every user on the social platform. Based on one’s past behavior, the algorithm predicts interests and recommends articles and notifications on Facebook News Feed. Similarly, the same concept applies when Amazon recommends “You might also like” products, or when Netflix recommends movies based on past behaviors.
While the terms Data Science, Machine Learning, and Artificial Intelligence are all closely interconnected, each has a distinct purpose and specific applications.
Artificial Intelligence means making machines intelligent to take decisions on their own according to the situation without the need for any human intervention, whereas Machine Learning is the approach to make those machines intelligent. Machine Learning algorithms enable machines to learn on their own without being explicitly programmed. Data science is an interdisciplinary field to extract knowledge or insights from data, Machine Learning and statistics are part of Data Science.
Data Scientist is one of the hottest professions of the century with the demand to shoot up by 28% by 2020 (source: IBM , May 2017). Apart from a Data Scientist, there are other growing roles like AI Engineer and Machine Learning Engineer in the industry that are closely related or advanced in the same career path. This Dual Master’s program learning path is designed in a way that it will help learners to land one of these prominent roles.