Data Science Certificate Course Modules

Module 1: Introduction to Data Science and the role of a Data Scientist

You will learn what data science is and why it is one of the hottest and most lucrative technical skills you can acquire. Data science is an essential part of any industry today, given the massive amounts of data that are produced. Data science's popularity has grown over the years, and companies have started implementing data science techniques to grow their business and increase customer satisfaction. You will understand the role of a Data Scientist entails and the different real-world use cases where data science is applied. We will also show you the various tools and techniques that Data Analysts use to provide insights for decision-making.

Module 2: Python for Data Science

Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. As part of our Data Science Certificate Fundamental Course, you will learn the fundamentals of Python. Python Fundamentals will cover Python Lists, Python Tuples, Python Dictionary, type conversion, Python operators, Python If Else, Python Loops, Arguments, Parameters and Lambda. We will also cover how to set up your environment for Python. It's possible to use Python without any additions, but there are quite a few open-source libraries that make Python data tasks much easier. We will show some popular and useful Python libraries for data scientists and engineers. We will cover Pandas, Numpy, Matplotlib and Seaborn packages.

Module 3: Statistics for Data Science

To become a successful Data Scientist, you must know your basics. Math and Statistics are the building blocks of Machine Learning algorithms. It is essential to know the techniques behind various Machine Learning algorithms to understand how and when to use them. Our Data Science Fundamental Certificate Course will cover the basics of Statistics that will give you the required knowledge to build machine learning and deep learning models.

Module 4: Building Machine Learning Models

Our Data Science Certificate Fundamental Course will cover both Supervised and Unsupervised Learning algorithms. Supervised Learning algorithms try to model relationships and dependencies between the target prediction output and the input features. We can predict the output values for new data based on those relationships that it learned from the previous data sets. We will cover some common Supervised Learning algorithms like Nearest Neighbor, Decision Trees, Linear Regression, Logistics Regression and Support Vector Machines (SVM). Unsupervised Learning is a machine learning technique in which the users do not need to supervise the model. We will cover some common Supervised Learning algorithms like K-Means clustering. We will build hands-on projects in areas like Prediction of 50 startups profit, Prediction of Gender Voice, Prediction Of Tumor Severity, Prediction of Diabetes Occurrence, Credit Card Clustering, etc.

Module 5: Introduction to Deep Learning

Deep Learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep Learning is a key technology behind driver-less cars, enabling them to recognize a stop sign or distinguish a pedestrian from a lamppost. It is key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. Our Data Science Certificate Fundamental Course will cover  Introduction to Deep Learning and Artificial Neural Network (ANN).

Module 6: Machine Learning on AWS SageMaker

AWS SageMaker was created with only one idea in mind: to put machine learning into every developer's hands, regardless of their knowledge of that area. It provides an easy, fast and scalable way to perform all three usual steps: build, train and deploy. The build step is done by connecting to other AWS services like S3 and transforming data in Amazon SageMaker notebooks. Train step is about using AWS SageMaker's algorithms and frameworks or bringing our own, for distributed training. Once training is completed, models can be deployed to Amazon SageMaker endpoints, for real-time or batch predictions. Our Data Science Certificate Fundamental Course will cover Introduction to AWS and How to build machine learning models on AWS SageMaker.

Module 7: Professional Development

You will get free access to our premium Career Mentoring Module (CV tips, Interview tips, LinkedIn, certifications, etc.) worth $200. Get invited to Career Day and Career Q & A from best-in-class speakers and world-class companies. Get updates on new 3rd-party jobs and internships when available.