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Data Analytics With Big Data

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Why Data Science from The Infinity Minds ?

Embark on a data science journey with Aifinite Learning, where you’ll receive specialized education, expert mentorship, practical projects, industry insights, and career assistance.

Key Features
  • Our courses are specifically designed to meet industry demands, ensuring you learn the most relevant skills.
  • Benefit from personalized mentorship and guidance from industry experts throughout your learning journey.
  • Gain practical experience through real-world projects, preparing you for challenges in the field.
  • Access insights and trends directly from industry professionals, helping you stay ahead of the curve.
  • Receive comprehensive support in job placement, resume building, and interview preparation to kickstart your career.

Course Curriculum

Designed by experts, our curriculum offers the perfect mix of knowledge and application to prepare you for real-world challenges.

  • 26 Weeks Program
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Excel for Data Science - 2 Weeks

Excel serves as a versatile tool in data science, facilitating data import, cleaning, analysis, and visualization. While beneficial for beginners and quick analyses, its limitations in handling large datasets and complex analyses are evident. Nonetheless, it remains a valuable component of the data science toolkit, often used in conjunction with other tools and languages for comprehensive data analysis workflows.

Structured Query Language (SQL) is a programming language used for managing and manipulating relational databases. It allows users to perform various operations such as querying data, updating records, inserting new data, and deleting data from databases. SQL is widely used in database management systems like MySQL, PostgreSQL, SQL Server, and Oracle. It provides a standardized way to interact with databases, making it an essential skill for data analysts, database administrators, and software developers working with relational databases.

Excel is a commonly used tool in data science for its accessibility and familiarity. It enables data scientists to perform tasks such as importing, cleaning, analyzing, and visualizing data. While Excel may not have the advanced capabilities of specialized data science tools, it remains valuable for quick exploratory analysis and visualization. Additionally, Excel’s integration with other tools and languages allows for more comprehensive data analysis workflows.

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Power BI / Tableau - 3 to 4 Weeks
Power BI and Tableau are leading data visualization tools used in data science and analytics. They enable users to create interactive dashboards, reports, and visualizations from diverse data sources. While Power BI offers seamless integration with Microsoft ecosystem and advanced features like natural language queries, Tableau provides a user-friendly interface and powerful analytics capabilities such as predictive analytics and storytelling. The choice between them often depends on specific business needs and user preferences.

Statistics involves analyzing data to extract insights, while hypothesis testing evaluates the validity of assumptions based on sample data. Both are crucial for making informed decisions in various fields, including data science.

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Pandas, Numpy, Seaborn - 3 Weeks
Pandas, NumPy, and Seaborn are essential Python libraries used extensively in data science and analysis. Pandas provides powerful data structures and tools for data manipulation and analysis, allowing users to handle structured data effectively. NumPy offers support for numerical computing, including arrays, matrices, and mathematical functions, making it ideal for scientific computing tasks. Seaborn is a data visualization library built on top of Matplotlib, providing a high-level interface for creating attractive and informative statistical graphics.
Machine learning is a branch of artificial intelligence where computers learn from data to make predictions or decisions without being explicitly programmed. It’s used in various applications such as image recognition, natural language processing, and predictive analytics, relying on algorithms to improve performance through experience.

In elective data science topics, “DL” covers Deep Learning for advanced neural network applications. “NLP” focuses on natural language processing. “Deployment” involves putting machine learning models into production. “Prompt Engineering” concerns crafting effective inputs for AI systems. These areas offer specialized skills for data scientists.

Upcoming Training Batch

  • The Course is ideal for:
  • Aspiring DevOps engineers, system administrators, and developers.
  • Tech enthusiasts aiming to leverage Python in automation and cloud computing.
  • Professionals looking to transition into roles focused on DevOps or AI-driven solutions.
  • Live Virtual Class
Feb 7 - April 4

10:00 AM - 02:00 PM IST

  • Certified Instructor

Weekend Batches - 16 Sessions

INR 29,999.00

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Course Certificate

To solve the problems of world class technology teams

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Curriculam Designed to Fit Your Organization

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Frequently Asked Questions

The eligibility of this program is that a person should have basic technical knowledge before he/she can start of with this program. Btech/ BCA/MCA candidates are preferred.

No, you do not have to pay the fees upfront. You only need to pay Rs2000/- for our flagship program for 2 week Abhyarthi phase and see how satisfied you are with pur course and teaching methodologies.

No, we currently have 2 courses. One is DevOps Ninja program. This is our flagship program. We also offer kubernetes program.

These are the three phases in which our DevOps ninja program is bifurcated into.

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