IBM - Data Science Professional Program Online Course

IBM - Data Science Professional Program

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Course Description

Unlock the Power of DataIn today's data-driven world, the ability to analyze and interpret complex data sets is crucial for informed business decisions. Our Data Science Professional Program is designed to equip you with essential skills and knowledge to excel in data science. From data analysis and visualization to machine learning and big data technologies, our comprehensive curriculum ensures you gain practical, hands-on experience. This IBM - Data Science Professional Program covers self-paced e-learning materials including course content, Lab/Assignment, hands on experience and Certification of IBM after completing the exam by IBM. -- Eligibility Criteria -- - 12th class or an equivalent level. - Inclination towards Programming. - A degree/diploma in engineering. - Any technical degree or experience as a working professional. - A bachelor’s or master’s degree in computer science.

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What you’ll learn

Python : Begin your journey with an in-depth understanding of Python, a powerful programming language used extensively in data science. This course covers the basics and helps you build a strong foundation for more advanced topics.
Introduction to Data Science / Data Science 101 : This course provides a comprehensive introduction to data science, covering fundamental concepts, methodologies, and the overall landscape. Learn the basics of data collection, cleaning, and exploration.
Python for Data Science : Delve deeper into Python with a focus on data science applications. This course teaches you to utilize Python libraries such as Pandas, NumPy, and SciPy for data manipulation and analysis.
Data Science Methodology : Understand the structured approach to solving data science problems. This course covers the data science lifecycle, from understanding the problem to deploying the model, ensuring a robust methodology.
Data Visualization with Python : Learn to create compelling visualizations using Python libraries like Matplotlib and Seaborn. This course emphasizes the importance of data visualization in interpreting and presenting data insights effectively.
Data Analysis with Python : Develop advanced data analysis skills using Python. This course covers statistical analysis, data wrangling, and exploratory data analysis techniques to draw meaningful insights from data.
Data Visualization with R : Explore data visualization techniques using R. This course introduces you to R libraries such as ggplot2, enabling you to create interactive and informative visual representations of data.
R for Data Science : Gain proficiency in R for data science applications. Learn to manipulate and analyze data using R, focusing on its powerful capabilities for statistical analysis and graphical representation.
Scala 101 : Discover the basics of Scala, a versatile programming language that integrates well with big data technologies. This course covers essential Scala concepts and prepares you for handling large-scale data processing.

Covering Topics

Learning Mode : Online Self-Paced (Learn Anywhere & Anytime).

Program Duration : 6 Months.

Learning Hours : 60+ (Includes E-Courseware, Videos, Hands-on-Labs, Assignments, Quiz etc by IBM).

Support : Weekly Doubt Clearance Session.

Certification : Official IBM certifications that directly engage with your LinkedIn Profile.

Curriculum

  Course 1 : Python

Module 1: Introduction to PYTHON 
Module 2: Deep dive into PYTHON
Module 3: Python Libraries
Module 4: Error Handling
Module 5: Other Topics
Module 6: Regression (Use case study)
Module 7: Other Regression related topics
Module 8: Advance

  Course 2 : Introduction to Data Science/ Data Science 101

Module 1: Defining Data Science
Module 2: What do data science people do?
Module 3: Data Science in Business
Module 4: Use Cases for Data Science
Module 5: Data Science People

  Course 3 : Python for Data Science

Module 1 : Python Basics
Module 2 : Python Data Structures
Module 3 : Python Programming Fundamentals
Module 4 : Working with Data in Python

  Course 4 : Data Science Methodology

Module 1 : From Problem to Approach
Module 2 : From Requirements to Collection
Module 3 : From Understanding to Preparation
Module 4 : From Modeling to Evaluation
Module 5 : From Deployment to Feedback

  Course 5 : Data Visualization with Python 

Module 1 : Introduction to Visualization Tools
Module 2 : Basic Visualization Tools
Module 3 : Specialized Visualization Tools
Module 4 : Advanced Visualization Tools
Module 5 : Creating Maps and Visualizing Geospatial Data

  Course 6 : Data Analysis with Python 

Module 1 : Importing Datasets
Module 2 : Cleaning and Preparing the Data
Module 3 : Summarizing the Data Frame
Module 4 : Model Development
Module 5 : Model Evaluation

  Course 7 : Data Visualization with R 

Module 1 : Basic Visualization Tools
Module 2 : Basic Visualization Tools Continued
Module 3 : Specialized Visualization Tools
Module 4 : How to create Maps
Module 5 : How to build interactive web pages

  Course 8 : R for Data Science

Module 1 : R basics
Module 2 : Data structures in R
Module 3 : R programming fundamentals
Module 4 : Working with data in R
Module 5 : Strings and Dates in R

  Course 9 : Scala 101

Module 1 : Introduction section
Module 2 : Basic Object Oriented Programming section
Module 3 : Case Objects and Classes section
Module 4 : Collections section
Module 5 : Idiomatic Scala section

Frequently Asked Questions

The program is designed to be completed in up to six months, depending on your pace and schedule.

Extremely flexible! The course is fully self-paced, allowing you to learn anytime, anywhere.

We provide dedicated doubt clearance sessions to ensure you have all the support you need throughout your learning journey.

Graduates are eligible for high-demand roles like Data Scientist, Data Analyst, Machine Learning Engineer, Business Intelligence Developer, and more.

Yes, candidates should have completed 12th grade, hold a technical degree/diploma, or be working professionals with an inclination toward programming.

We provide 100% job assistance, including resume building, interview preparation, and connecting you with potential employers in the industry.

Yes, you can download and access select course materials offline for convenience and continued learning.

You’ll gain expertise in Python, data analysis, machine learning, data visualization, R programming, big data technologies, and more to excel in data science roles.

All courses are self-paced, providing you the convenience to learn at your own speed with structured guidance.

Complete all course modules, pass the online exams administered by IBM, and you will earn globally recognized IBM certifications.