BCIT World is one of the best data science institutes in Patna. We provide both theoretical and practical sessions. We've trained over 1,000 students in classrooms and over 100 online. 🚀 Want to boost your data science skills for a rewarding career? 🤩 Join BCIT WORLD and learn everything you need for success! 🌟 From data visualization 📊 to machine learning 🤖 and ML Ops, we've got you covered! 💼 Start your data science journey with us today! 🚀 If you're looking for the best Data Science Training Institute in Patna, your search ends here. Join BCIT World for a free demo of our Data Science training with a live project internship!
High Demand for Skills: Data analyst are in high demand across various industries. Learning Data Science can open up many job opportunities.
Data-Driven Decisions: With Data Science , you can help organizations make better, data-driven decisions. This can lead to improved efficiency and profitability.
Versatile Career Options: Data Science skills are versatile and applicable in many fields, such as finance, marketing, healthcare, and technology.
Problem-Solving Skills: Learning Data Science enhances your problem-solving and critical-thinking skills, which are valuable in any career.
There are several reasons why you might consider taking an Data Science course:
The 6 best Job you can do after Learning Data Science Course:
The Data Science training programs are designed to give you a very good practical learning experience and develop skills that will be very useful for your career.
| Sl.No. | Course Name |
|---|---|
| Module.1 | Data Science Essentials |
| . | Fundamentals of Python |
| . | Fundamentals of mathematics |
| . | Linear algebra & probability |
| . | Measures and Descriptors of data |
| . | Distributions and Estimation |
| . | Hypothesis testing and Evaluation |
| Module.2 | Communicating Effectively with data |
| . | Exploratory Data Analysis |
| . | Data and Information System |
| . | Storytelling with data |
| . | Designing Business Dashboard |
| Module.3 | Optimisation for Machine Learning |
| . | Optimisation Formulations |
| . | Gradient and Scorch based Optimisation for Machine Learning |
| . | Linear Programming |
| . | Multi-objective and multi-criteria |
| . | Decision-making -Evolutionary Tools |
| Module.4 | Machine Learning |
| . | Linear Regression |
| . | Logistic Regression |
| . | Polynomial Regression |
| . | Decision- Tres, Random Forest |
| . | KNN, K-means clustering |
| . | Support Vector Machine |
| . | Dimensionality Reduction PCA |
| Module.5 | Deep Learning |
| . | Deep Forward Neural |
| . | Convolutional Neural |
| . | LSTM |
| . | RNN |
| . | Word 2 Vec |