MIS Global Technologies

COURSE

Data Science

Typically, a data science course gives participants the tools they need to glean insightful information from large, complicated databases. This course, which covers statistical analysis, machine learning, and data visualisation, equips students to solve problems in the real world and come to data-driven conclusions. In the rapidly developing field of data science, practical projects and hands-on experience improve expertise in essential tools and procedures.

5-days Online Class

Beginner

English

Introduction to Data Science

The interdisciplinary area of data science makes use of scientific procedures, systems, algorithms, and methodologies to glean valuable information from both structured and unstructured data.

What will you learn?

Data Science Certification

To earn your Data Science certification, you’ll need to pass one certification exam: Data Science Certification

Program Outcome

In this course, you will apply information Prompt Engineering in a number of scenarios:

Instructor-Led Training

An instructor-led training session, whether in-person or online, is base on classroom.

E-Learning

Learners can go through the content and activities at their own pace.

Hybrid Training

Combines traditional, face-to-face “seat time” with some online learning activities.

Curriculum | Your study plan

  • Introduction to data science concepts and applications
  • Basics of programming using Python.
  • Overview of data ethics and privacy considerations
  • Techniques for data cleaning and preprocessing
  • Data manipulation using Pandas (Python).
  • Statistical analysis and visualization using tools like Matplotlib and Seaborn
  • Exploring data patterns and relationships
  • Introduction to relational databases and SQL
  • Writing SQL queries for data extraction and manipulation
  • Overview of machine learning concepts and algorithms
  • Building and evaluating basic machine learning models
  • Feature engineering and selection techniques
  • Model evaluation, hyperparameter tuning, and avoiding overfitting
  • Application of learned skills in a real-world data science project
  • Presentation of findings and insights
  • Career development, including resume building and job search strategies

Testimony | What our students said?

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