Professional Certification Program in Data Science

Embark on a transformative 4-month journey into data science with "Data Science Foundations." Acquire proficiency in Python and R for data manipulation, visualization, statistical analysis, and machine learning. The course's hands-on approach, featuring real-world datasets, ensures practical application, fostering not only technical expertise but also critical thinking and communication skills.

Guided by machine learning principles, participants progress through optimizing predictive models and refining algorithms. Integrating critical thinking and effective communication, graduates emerge well-versed in the complexities of data science. The course culminates in a capstone project, where participants showcase their mastery by addressing a real-world challenge, preparing them to derive insights, make informed decisions, and contribute meaningfully to the evolving field.

Whether you're a beginner or a professional seeking skill augmentation, "Data Science Foundations" provides a transformative experience. Graduates leave with a profound understanding of the data science workflow, equipped to navigate intricate datasets, make impactful decisions, and thrive in the dynamic, data-driven landscape.

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5298+ Enrolled Students

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11^th Nov, 2023 Next Batch Start On

4 Months Live course

Skill Developement

11^th Nov, 2023 Next Batch Start On

Key Features

Zenrita Digital Academy stands as your gateway to excellence in data science. Immerse yourself in our meticulously crafted platform, where every detail is considered to shape you into a true Data Rockstar. Your journey with us promises not just education but a fulfilling career in the dynamic world of Data Science. Join us and let's pave the way to your success together!

400+ Hours of Instructor-Led Training

Dedicated Career Coach

150+ Hours of Self Paced Training

Professional Certification Program

500+ Exercises and Assesment

24/7 Support

Course Curriculum

Unleash Your Inner Data Rockstar! Our meticulously designed course curriculum leaves no stone unturned, guiding you through a comprehensive journey towards a promising and fulfilling Data Science career. Join us and embark on a transformative learning experience that sets the stage for your success in the dynamic world of data.

Fundamentals of Programming with Python
- Basics of Python syntax and data types
- Control structures and functions
- Hands-on coding exercises for proficiency
Fundamentals of Data Manipulation and Visualization
- Introduction to Pandas for data manipulation
- Working with NumPy arrays for numerical operations
- Practical exercises for effective data handling
- Creating basic visualizations using Matplotlib
- Advanced data visualization with Seaborn
- Project work to reinforce visualization skills
Statistical Analysis and Hypothesis Testing
- Key statistical concepts for data analysis
- Application of statistical methods in data science
- Real-world scenarios for hands-on practice
- Understanding hypothesis testing principles
- Practical application in data-driven decision-making
- Statistical analysis using Python and R
Machine Learning Fundamentals
- Overview of machine learning concepts and algorithms
- Supervised and unsupervised learning approaches
- Practical applications in real-world scenarios
Natural Language Processing (NLP)
- Basics of text processing and tokenization
- Sentiment analysis and text classification
- NLP applications in data science projects
Applied Machine Learning Techniques
- Implementing machine learning for solving practical challenges
- Feature engineering and optimization techniques
- Developing predictive models with scikit-learn
Model Optimization and Algorithm Refinement
- Strategies for optimizing predictive models
- Fine-tuning machine learning algorithms
- Practical exercises and case studies for mastery
Capstone Project: Real-World Data Challenge
- Applying acquired skills to address a real-world data challenge
- Independent or group project work
- Presentation of findings and insights
Soft Skills Development
- Applying critical thinking to data analysis
- Effectively communicating complex data insights
- Collaborative project work and peer feedback
Continuous Learning and Industry Trends
- Staying abreast of evolving data science trends
- Resources for continuous learning and professional development
- Networking opportunities and industry insights

Comprehensive Curriculum

The curriculum has been designed by faculty from Expert Industry Professionals

500+ Hours of Content

160+ Live Sessions

20+ Tools & Software

The Zenrita Digital Academy Advantage

Unlock the realm of practical Data Science applications and cultivate the skills essential for a thriving career in the field. Prepare for success with unparalleled support, personalized guidance, and immersive training experiences.

Tailored Support and Guidance

Unlimited 1:1 Doubt Clearing Sessions
Personalized Student Support
Engage in Hackathon Challenges to refine your talents
Showcase your skills with a dedicated E-portfolio
Personalized Personality Development Classes

Learn from Experts

Live online classrooms led by top Data Science educators in the industry
24/7 Support from Teaching Assistants for Assignment Help, Discussions, and Doubt Resolutions

Industry Leaders for Professional Development

Discover the inner workings of the Data Science industry.
Learn the crucial elements for success in the field.
Engage directly with seasoned Data Science professionals.

Networking for Career Growth

Foster your career alongside like-minded, highly motivated peers
Discover how our alumni embarked on their journeys in the ever-evolving field of Data Science

Key Features

Course Curriculum

Module 1: Introduction to Python

Module 2: Data Manipulation with Pandas and NumPy

Module 3: Data Visualization with Matplotlib and Seaborn

Module 4: Fundamentals of Statistics

Module 5: Hypothesis Testing in Data Science

Module 6: Introduction to Machine Learning

Module 7: Introduction to NLP

Module 8: Applying Machine Learning to Real-World Problems

Module 9: Techniques for Model Optimization

Module 10: Capstone Project

Module 11: Integrating Critical Thinking and Communication

Module 12: Staying Updated in Data Science