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Professional Data Engineering Course with Placement Assistance

  • 100% Job Guarantee Program
  • INR 6.9 LPA Conditional Job Offer Letter From Reputed AI Company
  • Post Graduate Diploma From The State University Of New York
  • Pan India and International Placement Support
  • No Prior Coding Experience? No Problem!

data science & AI course reviews - 360digitmg

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data science & Ai course reviews - 360digitmg

3472 Learners

Eligibility

College Degree in STEM related fields – Science, Mathematics, Engineering, Software Technology and Business.

No programming knowledge needed. You will learn from scratch!

Who should sign up?

  • Those aspiring to be Data Scientists, AI Experts, Business Analysts, Data Analytics, Software Developers
  • Graduates looking for a career in Data Science, Machine Learning, Forecasting, AI
  • Professionals migrating to Data Science
  • Academicians and Researchers
  • Students entering the IT industry

What Do You Learn

  • Learn to create Python constructs for the purpose of performing analytics
  • Connect with varied databases using Python and execute queries through SQL & NoSQL
  • Get a grip of the fundamentals of Mathematics & Statistics that are pertinent to Data science
  • Acquire the skill required for executing Machine Learning algorithms (Supervised & Unsupervised) and gather insights from the outcome
  • Learn about Cloud Computing skills and run Machine Learning algorithms on Cloud
  • Unbox the black box, demystify the concepts around Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, etc.
  • Learn to use one of the most popular open-source distributed data platform to enable storage and processing Big Data using commodity Hardware
  • Learn about analyzing unstructured data including Images, Videos, Audio, Text, and how to draw insights from the same
  • Stay ahead by learning to use optimized forecasting techniques and the various method for the same
  • Work with Data Plumbing to ensure a continuous flow of the real-time and or batch data in Data systems to make real-time decision making
  • Map End-to-End Machine Learning Models on Microsoft Azure cloud services for scalable and ready to Market solutions on Big Data
  • Work with one of the most popular visualization and business intelligence tools, Power BI, to make state of the art presentations and analytics
  • Learn AutoML libraries & frameworks – both open source and commercial. This includes building End-to-End pipelines of data related projects

After Successfully completing the programme you should be able to

  • Have a firm grip on the fundamentals of Machine Learning, Deep Learning, Cloud Platforms, DevOps for Data Science, Big Data, Database Management (SQL, NoSQL), Business Intelligence and many more
  • Successfully contribute towards Data Analytics projects involving ML, Cloud Computing and Data Pipeline building
  • Lead team of Analytics professionals with myriad experiences and efficaciously deliver the client requirements with the final objective in mind

Synopsis of Professional Data Engineering Course

This program is designed for Graduates who are keen on leveraging on the Analytics Knowledge and the valuable PG diploma from the leading university of the US. This blended program over the best of a multitude of courses, explains in detail, without compromising on the content quantity or quality.

A typical participant will be exposed to the rigors of multi-platform training that will encompass live virtual classes, prerecorded lectures, interactive chat support, mentoring, projects (end to end capstone and mini projects), pre assessments, post assessment, quizzes, and much more.

The program is also suited for both new graduates as well as working professionals who are looking to catapult their careers into a much higher league with the knowledge base acquired.

Curriculum of Professional Data Engineering Course

Chart Your Career with Industry Specific blended Core Modules Designed for Expanding Job Roles

Foundations of Data Engineering

Goal: Establish strong fundamentals in databases, data modeling, and core data engineering concepts.
Topics:

  • Role of a Data Engineer vs. Data Scientist vs. Data Analyst

  • Data life cycle & architecture overview

  • Relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra)

  • Data modeling techniques (star schema, snowflake schema, normalization/denormalization)

  • SQL for querying, joins, aggregation, window functions

  • Basic Linux shell scripting for data manipulation

Data Ingestion & Integration

Goal: Learn how to acquire, ingest, and integrate data from various sources.
Topics:

  • Batch ingestion (CSV, JSON, Parquet, Avro)

  • Streaming ingestion (Kafka, Kinesis, Pulsar)

  • APIs (REST & GraphQL) and web scraping

  • ETL vs. ELT concepts

  • Change Data Capture (CDC) techniques

  • Hands-on: building ingestion pipelines with Python & Apache Airflow

Data Storage & Warehousing

Goal: Master storing and organizing data for analytical workloads.
Topics:

  • Data lake vs. data warehouse vs. data lakehouse

  • Cloud storage (AWS S3, GCP Cloud Storage, Azure Blob)

  • Data warehouse tools (Snowflake, BigQuery, Redshift)

  • Columnar storage formats (Parquet, ORC)

  • Partitioning, clustering, indexing

  • Designing scalable schemas for analytics

Data Processing & Transformation

Goal: Learn to clean, transform, and process large datasets efficiently.
Topics:

  • Batch processing with Apache Spark & PySpark

  • Streaming processing with Spark Structured Streaming, Flink

  • Data cleaning & preprocessing best practices

  • Window functions & aggregation at scale

  • Data enrichment & feature engineering for ML pipelines

  • Orchestration with Apache Airflow / Prefect

Data Governance, Security & Quality

Goal: Ensure data is trustworthy, secure, and compliant.
Topics:

  • Data quality frameworks (Great Expectations, dbt tests)

  • Data governance principles (cataloging, lineage, stewardship)

  • Metadata management (Apache Atlas, DataHub)

  • Security (encryption, IAM, access control)

  • Compliance (GDPR, HIPAA)

  • Data versioning with tools like Delta Lake or lakeFS

Capstone Project & Career Preparation

  • End-to-end business analytics project

  • Real-world case studies with domain context

  • Resume building, mock interviews

  • Analytics roles & career path support

Industry Projects in collaboration with DERIVE

DERIVE provide customised and innovative solutions for the clients. The organisation is keen to support and encourage upcoming data professionals and they believe that the need for skilled data scientists in only going grow in the coming years. Fuzen IT in collaboration with DERIVE offers hands-on Internships to students where they can work on real world problems and solve real-world challenges.

Career Transition Stories

Lokesh

FUZEN IT has an exceptional team of instructors who supported and motivated me throughout course. Coming from a statistical background, I was initially unsure about programming—but their hands-on teaching helped me build strong coding skills. The career support team guided me throughout my job search, and I secured two great job offers. This course truly elevated my skills. It’s one of the best investments I’ve made in myself—completely worth it

Industry Trends

  • 68% career Transition
  • The average starting salary for Freshers on "Data Sciences" Start from Rs 8.5L* PA
  • Average Hike for "Data Scientist" stands at 34% to 50%

Programming Languages & Tools Covered

tesseract
tensorflow
tableau
python
powerbi
opencv
numpy
excel
jupyter
matplotlib
nltk

Our Alumni Work At

FAQs

The duration varies based on the learning pace, but typically, the program can be completed within a structured timeframe.

Not necessarily. Many of our beginner-level courses are designed for freshers and non-IT students. However, for advanced programs like AI and Cybersecurity, a basic understanding of programming is helpful

Yes. All enrolled students receive lifetime access to course materials, resources, and updates even after completing the course.

You can reach out through our contact page, WhatsApp support, or visit our nearest branch for one-on-one guidance.

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