#learn apache

[heart-ghost-studyblr]

I try to make a balance between reading the book "Kafka: The Definitive Guide - 2nd Edition," doing Confluent course lab exercises, and a little bit of Udemy projects with Kafka as well. In the middle of the week, I'm making my homepage to showcase some portfolio stuff, which is not my priority at this time, but it involves a lot of coding as well.

Feeling like I can answer any interview questions about Kafka at this point, including the fundamentals, use cases, and examples of writing a pub/sub system in Java.

It's all about studying; it magically changes you inside and out. You're the same person, in the same place, but now capable of creating really good software with refined techniques.

[being-mughal]

Blog Post 23: Getting Curious About Lighting

Etihad Airways continued to fascinate me while I undertook work with APACHE. My research into lighting tutorials went further to explore the interaction between fog volumes and emissives and post-process volumes to set the mood of virtual environments.

One of my experimental exercises included deleting the entire geometry before working with light and fog effects. It felt poetic. I began considering whether lighting art specialization would be a good match for me.

Reference: Faucher, W. (2024) Lighting for Mood & Atmosphere in Unreal Engine. Availabl

[horsemage]

Strong contender for my new favorite tortured astronomy acronym

[hebrewbyinbal]

Are you ready to embark on a Hebrew-learning journey like no other?

Welcome to Hebrew by Inbal, where I bring you a one-of-a-kind approach to learning the Hebrew language.

As a native Israeli living in Europe and the US, I understand the unique challenges faced by English speakers like you.

I've honed my teaching methods to simplify complex subjects and bridge the gap between Hebrew and English.

I take a revolutionary approach to learning Hebrew. Here's what sets me apart:

1. **Unique Methods** I've developed teaching methods and approaches that you won't find anywhere else. My expertise in both English and Hebrew allows me to create a seamless learning experience tailored to the English-speaking mind.

2. **Clear and Conversational** Just like a friend chatting with you face to face, I make sure my lessons are clear, conversational, and relatable. You're not alone on this journey; I've got your back.

3. **Conversational Fluency** If speaking and understanding Hebrew is your priority, look no further. Practically Speaking Hebrew is my transformational course packed with the value of a full academic year (for a fraction of the price) providing you with the practical skills you need to communicate effectively.

4. **Complete Reading and Writing Skills** If your goal is to read and write Hebrew fluently, my best-selling workbooks and textbooks—Hebrew 1, 2, and 3—are your ticket to success. These comprehensive resources will equip you with the skills you need like no other materials can.

5. **Personal Connection** I believe in forming a personal relationship with each of my students. I understand your fears, challenges, and obstacles in learning a new language, and I'm here to help you overcome them. Together, we'll navigate the trenches of language learning.

So, whether you're looking to read and write Hebrew like a pro or engage in meaningful conversations, visit HEBREWBYINBAL.COM today and choose your goal > Grab the resources that suit your needs, and let's embark on this incredible Hebrew-learning journey together.

I can't wait to see you succeed!

[vengoai]

In 2013, Databricks was born out of UC Berkeley with one mission: simplify big data and unleash AI through Apache Spark. Founders like Ali Ghodsi believed the future of computing lay in seamless data platforms. With $𝟑𝟑 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 in early backing from Andreessen Horowitz and NEA, Databricks introduced a cloud-based environment where teams could collaborate on data science and machine learning. By 2020, it had over 𝟓,𝟎𝟎𝟎 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬, including Shell and HP. Its 2023 funding round pushed its valuation to $𝟒𝟑 𝐛𝐢𝐥𝐥𝐢𝐨𝐧, cementing it as a leader in the AI infrastructure space. Databricks now powers analytics for over 𝐨𝐯𝐞𝐫 𝟓𝟎% of Fortune 500 companies.

The moral? When you streamline complexity, you don’t just sell software—you unlock transformation.

[sunbeaminfo]

Are you looking to build a career in Big Data Analytics? Gain in-depth knowledge of Hadoop and its ecosystem with expert-led training at Sunbeam Institute, Pune – a trusted name in IT education.

Why Choose Our Big Data Hadoop Classes?

🔹 Comprehensive Curriculum: Covering Hadoop, HDFS, MapReduce, Apache Spark, Hive, Pig, HBase, Sqoop, Flume, and more. 🔹 Hands-on Training: Work on real-world projects and industry use cases to gain practical experience. 🔹 Expert Faculty: Learn from experienced professionals with real-time industry exposure. 🔹 Placement Assistance: Get career guidance, resume building support, and interview preparation. 🔹 Flexible Learning Modes: Classroom and online training options available. 🔹 Industry-Recognized Certification: Boost your resume with a professional certification.

Who Should Join?

✔️ Freshers and IT professionals looking to enter the field of Big Data & Analytics ✔️ Software developers, system administrators, and data engineers ✔️ Business intelligence professionals and database administrators ✔️ Anyone passionate about Big Data and Machine Learning

[freddynossa]

Plataformas de Aprendizaje Automático: Las Herramientas que Impulsan la Revolución de la IA

  El aprendizaje automático (Machine Learning) se ha convertido en uno de los campos más dinámicos y transformadores de la tecnología moderna. Detrás de cada avance en inteligencia artificial, desde el reconocimiento facial hasta los vehículos autónomos, se encuentran potentes plataformas de software que permiten a desarrolladores e investigadores crear, entrenar y desplegar modelos de IA cada…

[jcmarchi]

DeepSeek-R1 reasoning models rival OpenAI in performance

New Post has been published on https://thedigitalinsider.com/deepseek-r1-reasoning-models-rival-openai-in-performance/

DeepSeek-R1 reasoning models rival OpenAI in performance

.pp-multiple-authors-boxes-wrapper display:none; img width:100%;

DeepSeek has unveiled its first-generation DeepSeek-R1 and DeepSeek-R1-Zero models that are designed to tackle complex reasoning tasks.

DeepSeek-R1-Zero is trained solely through large-scale reinforcement learning (RL) without relying on supervised fine-tuning (SFT) as a preliminary step. According to DeepSeek, this approach has led to the natural emergence of “numerous powerful and interesting reasoning behaviours,” including self-verification, reflection, and the generation of extensive chains of thought (CoT).

“Notably, [DeepSeek-R1-Zero] is the first open research to validate that reasoning capabilities of LLMs can be incentivised purely through RL, without the need for SFT,” DeepSeek researchers explained. This milestone not only underscores the model’s innovative foundations but also paves the way for RL-focused advancements in reasoning AI.

However, DeepSeek-R1-Zero’s capabilities come with certain limitations. Key challenges include “endless repetition, poor readability, and language mixing,” which could pose significant hurdles in real-world applications. To address these shortcomings, DeepSeek developed its flagship model: DeepSeek-R1.

Introducing DeepSeek-R1

DeepSeek-R1 builds upon its predecessor by incorporating cold-start data prior to RL training. This additional pre-training step enhances the model’s reasoning capabilities and resolves many of the limitations noted in DeepSeek-R1-Zero.

Notably, DeepSeek-R1 achieves performance comparable to OpenAI’s much-lauded o1 system across mathematics, coding, and general reasoning tasks, cementing its place as a leading competitor.

DeepSeek has chosen to open-source both DeepSeek-R1-Zero and DeepSeek-R1 along with six smaller distilled models. Among these, DeepSeek-R1-Distill-Qwen-32B has demonstrated exceptional results—even outperforming OpenAI’s o1-mini across multiple benchmarks.

MATH-500 (Pass@1): DeepSeek-R1 achieved 97.3%, eclipsing OpenAI (96.4%) and other key competitors.  

LiveCodeBench (Pass@1-COT): The distilled version DeepSeek-R1-Distill-Qwen-32B scored 57.2%, a standout performance among smaller models.  

AIME 2024 (Pass@1): DeepSeek-R1 achieved 79.8%, setting an impressive standard in mathematical problem-solving.

A pipeline to benefit the wider industry

DeepSeek has shared insights into its rigorous pipeline for reasoning model development, which integrates a combination of supervised fine-tuning and reinforcement learning.

According to the company, the process involves two SFT stages to establish the foundational reasoning and non-reasoning abilities, as well as two RL stages tailored for discovering advanced reasoning patterns and aligning these capabilities with human preferences.

“We believe the pipeline will benefit the industry by creating better models,” DeepSeek remarked, alluding to the potential of their methodology to inspire future advancements across the AI sector.

One standout achievement of their RL-focused approach is the ability of DeepSeek-R1-Zero to execute intricate reasoning patterns without prior human instruction—a first for the open-source AI research community.

Importance of distillation

DeepSeek researchers also highlighted the importance of distillation—the process of transferring reasoning abilities from larger models to smaller, more efficient ones, a strategy that has unlocked performance gains even for smaller configurations.

Smaller distilled iterations of DeepSeek-R1 – such as the 1.5B, 7B, and 14B versions – were able to hold their own in niche applications. The distilled models can outperform results achieved via RL training on models of comparable sizes.

🔥 Bonus: Open-Source Distilled Models!

🔬 Distilled from DeepSeek-R1, 6 small models fully open-sourced 📏 32B & 70B models on par with OpenAI-o1-mini 🤝 Empowering the open-source community

🌍 Pushing the boundaries of **open AI**!

🐋 2/n pic.twitter.com/tfXLM2xtZZ

— DeepSeek (@deepseek_ai) January 20, 2025

For researchers, these distilled models are available in configurations spanning from 1.5 billion to 70 billion parameters, supporting Qwen2.5 and Llama3 architectures. This flexibility empowers versatile usage across a wide range of tasks, from coding to natural language understanding.

DeepSeek has adopted the MIT License for its repository and weights, extending permissions for commercial use and downstream modifications. Derivative works, such as using DeepSeek-R1 to train other large language models (LLMs), are permitted. However, users of specific distilled models should ensure compliance with the licences of the original base models, such as Apache 2.0 and Llama3 licences.

(Photo by Prateek Katyal)

See also: Microsoft advances materials discovery with MatterGen

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: ai, artificial intelligence, benchmark, comparison, deepseek, deepseek-r1, large language models, llm, models, reasoning, reasoning models, reinforcement learning, test

[tahomawhisperingwind]

Crafting Connections: Workshops on Traditional Apache Crafts for Kids

Image generated by the author

Imagine a sun-drenched afternoon in the heart of the Southwest, where the air is infused with the earthy scent of clay and the gentle rustle of natural grasses fills the air. Laughter rings out as children’s hands delve into the rich textures of traditional Apache crafts—pottery shaping beneath fingers, vibrant beads sparking creativity, and intricate baskets beginning to take form. These are not just workshops; they are gateways to a cultural legacy, where the past intertwines with the present, and the wisdom of the Apache people is passed down to a new generation.

The Workshop Experience: An Immersive Cultural Journey

In today’s fast-paced world, where screens often dominate children's attention, the Apache crafts workshops provide a much-needed pause. They offer a rare opportunity for young participants to engage with their cultural roots through hands-on experiences that transcend mere learning. Here, children dip their hands into the clay, feeling its coolness, and weave with grasses, allowing their imaginations to flourish. Each workshop is designed to be a profound journey, inviting kids to explore not only the art of crafting but also the philosophies and stories that underpin these age-old traditions.

Participating in activities such as pottery making, basket weaving, and intricate beadwork, children are not just creating; they are connecting. Each crafted item becomes a vessel of Apache wisdom, encapsulating stories of ancestors, the land, and the intricate relationship between humans and nature. The workshops encourage children to slow down, to appreciate the beauty of craftsmanship, and to foster a deeper understanding of their heritage.

The Cultural Context: Weaving History into Craft

The Apache people have a rich history that is intricately woven with their traditional crafts. Every craft tells a story—a narrative punctuated by resilience, survival, and an unwavering connection to the earth. Pottery, for instance, is not merely a functional object; it represents generations of knowledge passed down through families, each piece echoing the voice of an ancestor. Basket weaving, similarly, reflects both artistic expression and practical skills honed over centuries, often utilizing materials sourced directly from the surrounding landscape.

Through these workshops, children delve into the significance of these crafts, learning that every weave and every shape is imbued with cultural meaning. They discover the importance of sustainability and environmental stewardship, understanding that the materials they use come from nature and should be treated with respect. In this way, the workshops serve as a bridge, helping to instill a sense of identity and cultural pride in the participants.

Crafting Values: Patience, Creativity, and Resilience

Crafting is not solely about the end product; it is a process that teaches invaluable life lessons. As children learn to weave baskets or mold clay into pottery, they cultivate patience and persistence. They encounter challenges, whether it’s overcoming a stubborn piece of clay or perfecting the tension in their weaving. Each struggle becomes a lesson in resilience, a reminder that mastery takes time and effort.

The workshops also encourage creativity. With each bead strung and each basket woven, children express themselves artistically. They learn that there are no strict rules; the beauty of art lies in personal expression. Collaborating with peers fosters camaraderie, as they share techniques and ideas, forging friendships that transcend cultural lines. This sense of community becomes a vital part of the experience, reinforcing the idea that crafting is a collective endeavor.

Storytelling: The Heartbeat of Apache Heritage

At the core of these workshops lies the art of storytelling. As children engage in crafting, they are immersed in Apache tales, legends, and teachings that enrich their understanding of the culture. Each crafted piece becomes more than just an object; it transforms into a narrative canvas, where personal stories and cultural histories collide.

As they weave their baskets, children might hear about the significance of the materials they use—how the grasses symbolize strength and flexibility. While shaping clay into pottery, they may listen to stories of ancestors who relied on these vessels for sustenance and survival. The storytelling aspect of the workshops enhances critical thinking, as children reflect on the lessons embedded in each narrative and relate them to their own lives.

Bridging the Past and Present: Modern Relevance of Apache Crafts

In a world dominated by digital distractions, these workshops offer a refreshing escape. They serve as a reminder of the importance of unplugging and reconnecting with the creative spirit that resides in each child. When hands are busy shaping clay or weaving fibers, minds become engaged in a way that screens cannot replicate.

Moreover, the workshops highlight the significance of environmental awareness. Children learn that traditional crafting practices are rooted in sustainability. They come to understand that respecting nature is not just a cultural obligation but a universal necessity. As they craft, they become stewards of the earth, learning the value of natural materials and the impact of their actions on the environment.

Conclusion: Nurturing Future Generations

As the sun sets on another day of crafting, the echo of laughter and joy lingers in the air. The workshops on traditional Apache crafts are more than mere activities; they are a profound investment in the future. They nurture a generation that not only appreciates Apache culture but also embodies the values of environmental stewardship and community engagement.

These experiences cultivate creativity, knowledge, and pride in heritage, ensuring that the traditional practices of the Apache people continue to thrive. The workshops invite us all to participate in this journey—whether by enrolling our children, volunteering, or simply spreading the word about the importance of cultural preservation.

As we reflect on the vibrant connection between past and present, we are left with a thought-provoking question: How can we each contribute to preserving the rich tapestry of our cultural heritage while fostering a deeper connection to the natural world? It is a call to action, a reminder that the stories we weave and the crafts we create today will shape the narratives of tomorrow.

AI Disclosure: AI was used for content ideation, spelling and grammar checks, and some modification of this article.

About Black Hawk Visions: We preserve and share timeless Apache wisdom through digital media. Explore nature connection, survival skills, and inner growth at Black Hawk Visions.

[rajaniesh]

Unveiling the Power of Delta Lake in Microsoft Fabric

Discover how Microsoft Fabric and Delta Lake can revolutionize your data management and analytics. Learn to optimize data ingestion with Spark and unlock the full potential of your data for smarter decision-making.

In today’s digital era, data is the new gold. Companies are constantly searching for ways to efficiently manage and analyze vast amounts of information to drive decision-making and innovation. However, with the growing volume and variety of data, traditional data processing methods often fall short. This is where Microsoft Fabric, Apache Spark and Delta Lake come into play. These powerful…

[heart-ghost-studyblr]

Another day in my way to become a apache kafka developer, sometimes I use the pomodoro technique to stay away from my phone and really like to take notes when learning and practive a few questions of the exam.

[being-mughal]

Blog Post 20: Submission & Panel Feedback

I decided AnimAPK export would not be ready in time so I developed a different solution. By utilizing Unreal editor viewport together with cinematic camera cuts I created a full VR simulation recording.

During my work I maximized the use of smooth transitions, fades and close-up shots for key areas inside the tomb. The simulation lacked VR functionality yet effectively simulated it through different camera angles.

This backup plan saved me. The change enabled me to create a final project that brought satisfaction.

[scholarnest]

SQL Course Training: Advancing Your Database Skills

In the realm of data analysis and management, SQL (Structured Query Language) stands as a foundational skill indispensable for professionals seeking to navigate and manipulate databases effectively. As the demand for data-driven insights continues to soar, honing your SQL proficiency through targeted training can significantly enhance your capabilities in data analysis and open doors to diverse career opportunities. Let's explore the significance of SQL course training and how it can advance your database skills.

Understanding the Importance of SQL in Data Analysis:

SQL serves as the universal language for communicating with relational databases, enabling users to retrieve, manipulate, and manage data efficiently. Whether you're a data analyst, data scientist, or database administrator, mastering SQL empowers you to extract valuable insights, perform complex queries, and optimize database performance. With its widespread adoption across industries, SQL proficiency has become a prerequisite for roles involving data analysis and database management.

Key Components of SQL Course Training:

SQL course training encompasses a range of topics tailored to equip learners with comprehensive database management skills. From basic SQL syntax to advanced query optimization techniques, these courses cover essential concepts and best practices for leveraging SQL effectively. Key components of SQL course training include:

- SQL Fundamentals: Understanding basic SQL commands, data types, and database objects.

- Querying Databases: Crafting SELECT statements to retrieve data from tables and apply filtering, sorting, and aggregation.

- Data Manipulation: Performing INSERT, UPDATE, DELETE operations to modify data within tables.

- Database Design: Understanding principles of database normalization, table relationships, and entity-relationship modeling.

- Advanced SQL Topics: Exploring advanced SQL features such as joins, subqueries, stored procedures, and triggers.

- Optimization and Performance Tuning: Techniques for optimizing SQL queries, indexing strategies, and enhancing database performance.

Choosing the Best SQL Course:

When selecting a SQL course online, it's essential to consider factors such as:

- Curriculum: Ensure the course covers a comprehensive range of SQL topics, from fundamentals to advanced concepts.

- Hands-On Practice: Look for courses that offer hands-on exercises and projects to reinforce learning and practical application.

- Instructor Expertise: Choose courses led by experienced SQL professionals with a track record of delivering high-quality instruction.

- Student Reviews: Assess feedback from past learners to gauge the course's effectiveness and relevance to your learning goals.

- Certification: Some SQL courses offer certification upon completion, which can validate your skills and enhance your credentials in the job market.

Integrating SQL with Data Analysis:

SQL proficiency synergizes seamlessly with data analysis tasks, enabling analysts to extract, transform, and analyze data stored in relational databases. Whether you're performing ad-hoc analysis, generating reports, or building data pipelines, SQL serves as a powerful tool for accessing and manipulating data effectively. By mastering SQL alongside data analysis skills and tools such as Python and Apache Spark, you can enhance your capabilities as a data professional and tackle complex analytical challenges with confidence.

Conclusion:

Investing in SQL course training is a strategic step towards mastering database management skills and advancing your career in data analysis. Whether you're a novice seeking to build a solid foundation in SQL or an experienced professional aiming to sharpen your expertise, there are ample opportunities to enhance your database skills through online SQL courses. By selecting the best SQL course that aligns with your learning objectives and investing time and effort into mastering SQL concepts, you can unlock new possibilities in data analysis and become a proficient database practitioner poised for success in today's data-driven world.

[mysticpandakid]

What is PySpark? A Beginner’s Guide 

Introduction 

The digital era gives rise to continuous expansion in data production activities. Organizations and businesses need processing systems with enhanced capabilities to process large data amounts efficiently. Large datasets receive poor scalability together with slow processing speed and limited adaptability from conventional data processing tools. PySpark functions as the data processing solution that brings transformation to operations.  

The Python Application Programming Interface called PySpark serves as the distributed computing framework of Apache Spark for fast processing of large data volumes. The platform offers a pleasant interface for users to operate analytics on big data together with real-time search and machine learning operations. Data engineering professionals along with analysts and scientists prefer PySpark because the platform combines Python's flexibility with Apache Spark's processing functions.  

The guide introduces the essential aspects of PySpark while discussing its fundamental elements as well as explaining operational guidelines and hands-on usage. The article illustrates the operation of PySpark through concrete examples and predicted outputs to help viewers understand its functionality better. 

What is PySpark? 

PySpark is an interface that allows users to work with Apache Spark using Python. Apache Spark is a distributed computing framework that processes large datasets in parallel across multiple machines, making it extremely efficient for handling big data. PySpark enables users to leverage Spark’s capabilities while using Python’s simple and intuitive syntax. 

There are several reasons why PySpark is widely used in the industry. First, it is highly scalable, meaning it can handle massive amounts of data efficiently by distributing the workload across multiple nodes in a cluster. Second, it is incredibly fast, as it performs in-memory computation, making it significantly faster than traditional Hadoop-based systems. Third, PySpark supports Python libraries such as Pandas, NumPy, and Scikit-learn, making it an excellent choice for machine learning and data analysis. Additionally, it is flexible, as it can run on Hadoop, Kubernetes, cloud platforms, or even as a standalone cluster. 

Core Components of PySpark 

PySpark consists of several core components that provide different functionalities for working with big data: 

RDD (Resilient Distributed Dataset) – The fundamental unit of PySpark that enables distributed data processing. It is fault-tolerant and can be partitioned across multiple nodes for parallel execution. 

DataFrame API – A more optimized and user-friendly way to work with structured data, similar to Pandas DataFrames. 

Spark SQL – Allows users to query structured data using SQL syntax, making data analysis more intuitive. 

Spark MLlib – A machine learning library that provides various ML algorithms for large-scale data processing. 

Spark Streaming – Enables real-time data processing from sources like Kafka, Flume, and socket streams. 

How PySpark Works 

1. Creating a Spark Session 

To interact with Spark, you need to start a Spark session. 

Output: 

2. Loading Data in PySpark 

PySpark can read data from multiple formats, such as CSV, JSON, and Parquet. 

Expected Output (Sample Data from CSV): 

3. Performing Transformations 

PySpark supports various transformations, such as filtering, grouping, and aggregating data. Here’s an example of filtering data based on a condition. 

Output: 

4. Running SQL Queries in PySpark 

PySpark provides Spark SQL, which allows you to run SQL-like queries on DataFrames. 

Output: 

5. Creating a DataFrame Manually 

You can also create a PySpark DataFrame manually using Python lists. 

Output: 

Use Cases of PySpark 

PySpark is widely used in various domains due to its scalability and speed. Some of the most common applications include: 

Big Data Analytics – Used in finance, healthcare, and e-commerce for analyzing massive datasets. 

ETL Pipelines – Cleans and processes raw data before storing it in a data warehouse. 

Machine Learning at Scale – Uses MLlib for training and deploying machine learning models on large datasets. 

Real-Time Data Processing – Used in log monitoring, fraud detection, and predictive analytics. 

Recommendation Systems – Helps platforms like Netflix and Amazon offer personalized recommendations to users. 

Advantages of PySpark 

There are several reasons why PySpark is a preferred tool for big data processing. First, it is easy to learn, as it uses Python’s simple and intuitive syntax. Second, it processes data faster due to its in-memory computation. Third, PySpark is fault-tolerant, meaning it can automatically recover from failures. Lastly, it is interoperable and can work with multiple big data platforms, cloud services, and databases. 

Getting Started with PySpark 

Installing PySpark 

You can install PySpark using pip with the following command: 

To use PySpark in a Jupyter Notebook, install Jupyter as well: 

To start PySpark in a Jupyter Notebook, create a Spark session: 

Conclusion 

PySpark is an incredibly powerful tool for handling big data analytics, machine learning, and real-time processing. It offers scalability, speed, and flexibility, making it a top choice for data engineers and data scientists. Whether you're working with structured data, large-scale machine learning models, or real-time data streams, PySpark provides an efficient solution. 

With its integration with Python libraries and support for distributed computing, PySpark is widely used in modern big data applications. If you’re looking to process massive datasets efficiently, learning PySpark is a great step forward. 

[sunbeaminfo]

Are you looking to build a career in Big Data Analytics? Gain in-depth knowledge of Hadoop and its ecosystem with expert-led training at Sunbeam Institute, Pune – a trusted name in IT education.

Why Choose Our Big Data Hadoop Classes?

🔹 Comprehensive Curriculum: Covering Hadoop, HDFS, MapReduce, Apache Spark, Hive, Pig, HBase, Sqoop, Flume, and more. 🔹 Hands-on Training: Work on real-world projects and industry use cases to gain practical experience. 🔹 Expert Faculty: Learn from experienced professionals with real-time industry exposure. 🔹 Placement Assistance: Get career guidance, resume building support, and interview preparation. 🔹 Flexible Learning Modes: Classroom and online training options available. 🔹 Industry-Recognized Certification: Boost your resume with a professional certification.

Who Should Join?

✔️ Freshers and IT professionals looking to enter the field of Big Data & Analytics ✔️ Software developers, system administrators, and data engineers ✔️ Business intelligence professionals and database administrators ✔️ Anyone passionate about Big Data and Machine Learning

Course Highlights:

✅ Introduction to Big Data & Hadoop Framework ✅ HDFS (Hadoop Distributed File System) – Storage & Processing ✅ MapReduce Programming – Core of Hadoop Processing ✅ Apache Spark – Fast and Unified Analytics Engine ✅ Hive, Pig, HBase – Data Querying & Management ✅ Data Ingestion Tools – Sqoop & Flume ✅ Real-time Project Implementation