Data Science with Python certification course in Pune. IABAC Certification | Become a Certified Data Scientist in 3 Months | 50 Hrs of Blended Learning | 3 Industry Projects | Placement Assured Program

1. Importance of Data
Science with Python
Certification Training
Data Science with Python Certification Training is crucial for professionals
aiming to excel in data analysis, machine learning, and artificial
intelligence. This certification provides in-depth knowledge of Python
programming and its various applications in data science, making it an
essential asset for anyone pursuing a career in this field.

2. What is Data Science?
Data Science is the field of study that combines domain expertise,
programming skills, and knowledge of mathematics and statistics to
extract meaningful insights from data. It involves the use of various tools
and techniques to analyze and interpret complex data sets.

3. Why Python for Data Science?
Python is widely used in data science due to its simplicity and versatility.
Its extensive libraries and frameworks make it ideal for data manipulation,
analysis, and visualization.
Python's readability and straightforward syntax make it accessible to
individuals from non-technical backgrounds.

4. Key components of the Certification
Training
• Comprehensive curriculum: In-depth coverage of Python, data analysis, machine learning, and
data visualization
• Hands-on projects: Practical exercises to apply concepts to real-world scenarios
• Industry-relevant case studies: Analysis of real industry data to solve complex problems

5. Curriculum Overview
1 Python Fundamentals
Covering basic syntax, data types, and control structures.
2 Data Analysis and Visualization
Using libraries like Pandas and Matplotlib for data exploration and
visualization.
3 Machine Learning and Deep Learning
Understanding algorithms and neural networks for predictive modeling.

6. Hands-on projects and case studies
During the certification training, participants will
engage in hands-on projects and case studies to
apply their data science and Python skills in real-
world scenarios. These practical exercises will
enhance their understanding and problem-
solving abilities, preparing them for real-life
challenges in the field.

7. Industry applications
Healthcare
Data science is used in healthcare to analyze
patient data, optimize treatment plans, and
improve patient outcomes.
Finance
Data science techniques are applied in finance for
fraud detection, risk assessment, and investment
strategies.

8. Career opportunities
Data Science
Roles
Data scientists, data
analysts, machine
learning engineers,
and AI specialists
are in high demand
across various
industries.
Industry
Applications
Opportunities in
finance, healthcare,
e-commerce, and
technology for
implementing data
science solutions
and strategies.
Growth Prospects
With the increasing
adoption of data-
driven decision-
making, the demand
for data science
professionals is
expected to grow
rapidly.
Specialized Roles
Specialized data
science roles such
as big data
engineers, data
architects, and data
visualization experts
offer diverse career
paths.

9. Certification Exam Details
1 Exam Format
The certification exam consists of multiple-
choice questions and practical coding
exercises.
2 Duration
Candidates will have 3 hours to complete
the examination.
3 Passing Criteria
To pass, candidates must achieve a
minimum score of 70% in both the theory
and practical components.
4 Exam Dates
The certification exam is offered on a
monthly basis, providing flexibility for
candidates' schedules.

10. Conclusion
Application of Skills
Apply the concepts and tools learned to real-
world projects and problems.
Certification Preparation
Review materials and practice test questions
for the certification exam.
Networking and Collaboration
Connect with peers for collaboration and stay
updated with industry trends.
Continuous Learning
Explore advanced topics and build on the
foundational knowledge gained.