Data Science With Generative AI Course

In this advanced Data Science Certification program, you will undergo 10+ Data Science Courses along with multiple case studies and industry-oriented project work.

Online Instructor-led Interactive Sessions:

• Course 1: Linux and Python Fundamentals
• Course 2: Data Wrangling with SQL
• Course 3: Python with Data Science
• Course 4: Linear Algebra and Advanced Statistics
• Course 5: Machine Learning and Prediction Algorithms
• Course 6: Supervised and Unsupervised Learning in ML
• Course 7: Deep Learning with Tensorflow
• Course 8: Generative AI & Prompt Engineering
• Course 9: Deploying Machine Learning Models on Cloud
• Course 10: Data Visualization Tool Power BI

Additionally, Data Science Capstone Projects and multiple electives will be provided to enhance your knowledge in the Data Science & AI domain with this data science course

In this data science course, you will master the key skills to become a successful data scientist, such as:

Linux: Learn basic Linux commands to gain expertise with Linux command line. Most of the production systems in the world runs on Linux.

Python For Data Science: Master practical skills with Python programming & its data science libraries like Pandas, Numpy, Matplotlib, etc. Get hands on with ETL (Extract, transform, Load) in this data science course.

Statistics: To become a successful data scientist, one needs to have decent knowledge of mathematics like linear algebra, & more.

Machine Learning: Master supervised and unsupervised algorithms with this program and solve business problems using algorithms.

Artificial Intelligence: Understand how neural network works, its implementation in the business. Work on projects & create your own AI applications.

Power BI: Master most widely used visualization tool by Microsoft. Learn how to create complex interactive dashboards and management reports.

MLOps: Once you have mastered the Machine Learning algorithms, it’s a time to deploy the machine learning model you have created on the cloud platform, like AWS or Azure.

MS Excel: Learn Excel analytics from scratch to master data transformation, data manipulation, data modelling and reporting.

Generative AI: Master prompt engineering and tools like ChatGPT to build data science application at lightning speed.

Data Scientists are in high demand and offered high-paying jobs. This allows for diverse career opportunities in data science, along with innovation and solving complex business problems. We live in an AI era where Data Scientists enjoy global job prospects and the ability to influence key decisions in the organization.

Some of the core responsibilities of data scientists are:

1. Understand the Problem: Data scientists should be aware of the business-pain-points and ask the right questions.
2. Collect Data: They collect enough data to understand the problem in a better manner.
3. Process the Raw Data: We rarely use data in its original form, and it must be processed. There are several ways to convert it into a usable format.
4. Explore the Data: After processing data and converting it in a usable form, data scientists must examine it to determine its characteristics and find evident trends, correlations, and more.
5. Analyse the Data: To understand the data, they use various tool libraries, such as machine learning, statistics and probability, time series analysis, and more.
6. Communicate Results: At last, results must be communicated to the right stakeholders, laying the groundwork for all identified issues.

Our data science certification course will help you to master data scientist skills in just 7 months.