Python Training classes near me in Tavarekere Main Road, Bangalore

Objectives – Having 18.5 years of experience As a Technical Lead and Architect, I am passionate about leveraging my expertise in Databricks, Data Build Tool, Spark, Confluent Kafka, Data Lake, Lake House and Cloud Solutions to drive innovation and efficiency. With a solid background in data architecture and IT Infrastructure, I am to contribute to the robust and vision of your company by providing ro bust technical solutions that align with strategic business goals. My Goal is to enhance data-driven decision-making processes, optimize big data pipelines and implement secure and scalable cloud architectures that people the organization forward in the ever-evolving technical landscape. Certification & Achievements – 1. Confluent Certified Administrator for Apache Kafka: expiry July 2026. Confluent Certified Administrator for Apache Kafka • Amit Raj • Confluent 2. Databricks Certified Data Engineer Professional: expiry Aug 2026 Databricks Certified Data Engineer Professional • Amit Raj • Databricks Badges 3. Databricks Accredited Lakehouse Fundamentals: expiry June 2025 Academy Accreditation - Databricks Lakehouse Fundamentals • Amit Raj • Databricks Badges 4. Microsoft Certified: Azure Administrator Associate (AZ104): Microsoft certification ID: 1100039942 Expires on: August 3, 2025 Credentials - AmitRaj-8869 | Microsoft Learn 5. Microsoft Certified: Azure Security Engineer Associate (AZ500): Microsoft certification ID: 1100039942 Expires on: August 6, 2025 Credentials - AmitRaj-8869 | Microsoft Learn 6. Recognition certificate from Fidelity for designing global solutions for Data exchange. 7. Got Achievement medal from DIB(Client) with appreciation for design event-based enterprise architecture & contribution – EventHub SUMMARY • Overall total of 18.5+ years of Experience years of Experience in Application Design, Development & Deployment of Hadoop Eco System/Java/J2EE systems with good exposure to Enterprise Architecture. • Relevant Experience 9.2 years in Big Data technologies working with multiple clients and domain knowledge. • Experienced in Cassandra data modelling, cluster setup and data management. • Experienced in working with Spark-SQL, Spark SQL and Spark Structure Streaming, MLib to process and analyse data queries. • Experienced in designing solutions using Spark Streaming and Kafka Streaming for Payment Gateway/point of sales events. • Individual Contribution (Kafka Architect): Delivered UAT and PROD Cluster within the timeline for Kafka cluster using Cloudera 6.x, CSP 2.0. • Implemented a unified data platform to gather data from different sources using Kafka Producers and consumers in Scala and java. • Solid background in Object-Oriented analysis & design, UML and various design patterns. • Worked using Azure cloud(Blob, EventHub), Kubernetes, docker with Spark, scala, Schema Registry, Avro Schema with home security application for Honeywell • Implemented KSQL, KTable and KStream using Confluent Kafka along with Kafka Connect. • Hands-on Data bricks - Databricks Clusters, Data Lakehouse, Delta lake, DBFS, EXPLORE, Analyze, Clean, Transform and Load Data using Databricks. • Experience with Azure: Azure Synapse Analytics, ADLS, ADF, CosmoDB, Azure Function, Stream Analytics, Power BI. • Experience with SQL and NoSQL databases including Mysql, Oracle, Cassandra, and PostgreSQL. BigTable • Experience building and optimizing the ‘big data’ data pipeline. • Experince with Azure Devops, CI/CD pipeline, Kubernetes and docker • Motivated Technical Architect with 5 years of progressive experience. • Having Experience AWS (Ec2,S3) • Having experience with Snowflake to design data lake and load data from multiple sources to the Snowflake database. • Effectively manages assignments and team members. • Dedicated to self-development to provide expectation-exceeding service. Customer-focused, successfully contributing to company profits by improving team efficiency and productivity. • Utilizes excellent organizational skills to enhance efficiency and lead teams to achieve outstanding delivery. SKILLS == ===================  Database architecture  Database architecture development  Data Architecture  Big Data ETL  Technical solution development  Azure data solutions  Data insight provision  Technical guidance  IT Architecture  Technical solutions  Big data frameworks Technical Skills: Hortonworks2.5, Cloudera5/6, Apache Hadoop2/3 ,Spark2/3,Apache Kafka, Confluent Kafka, Hive 2/3, Impala, Sqoop, OOZie, Zookeeper, Snowflake, Data Build tool (DBT), HBase, Apache Cassandra /DataStax Cassandra, Data Bricks, Azure Cloud, AWS cloud, Talend, Airflow etc. Programming Language Python , Scala & Java Other Tools Kibana, Logstash, ElasticSearch, ELK. ============================= PROJECT UNDERTAKEN: Project: Implementation of Data Warehouse and reporting platform Roles: Databricks Architect & Engineer Teams: 12 members Technical Skills: Azure Cloud, Azure Data Factory (ADF), ADLS, Databricks, Spark3.x, Python, Scala2.15, DB2, Oracle 12g, Azure SQL My Contribution Data Bricks Infrastructure Solution: - Configured Unified Data Access Control using Unity Catalog – E1 & BY System provide a specific set of permissions, like Read Only, or, Write Only to a specific Group of Users on one, or, some of the Delta Tables, or, even at the Row Level, or, Column Level, which can contain Personally Identifiable Information, i.e., PII, of that Delta Tables - Provide Data Governance with centralized place: administer (TAI) the access to the data, and, also audit the access to the data. - Applied Data lineage for E1 & BY tables with look-up tables using Unity Catalog. - Implemented Data sharing protocol to apply secure data sharing downstream using Unity Catalog and - Design Architecture of Unity Catalog which can be linked to multiple Databricks Workspaces- DEV, UAT, PROD environment. - Created Metastore for the Unity Catalog - Apply User Management of the Unity Catalog for the TAI Lakehouse project: Users, Groups, or, the Service Principle, and, the permissions those have - Configure Data Bricks Cluste with spark 3.x for DEV, UAT & PROD for TAI -E1 & BY System. - Design & apply medallion architecture, Setup a Data Lake house with Bronze, Silver and Gold layers of a storage system using Azure Data Lake Gen2. Azure Cloud Infra and Security: - Install self-hosted integration runtime for the DB2 ON DEV, UAT & PROD and Oracle on-prem cluster on the source system. - Install Azure Virtual network managed IR On DEV, UAT & PROD. - Installed Db2 connector on DEV, UAT & PROD. - Created linked service lnk_BY_Azure_SQL, lnk_E1_Azure_SQL, lnk_Db2_E1 - Install and Configure Azure Key-Vault, added all the credential for Azure SQL, ADLS, Databricks, Users, global users, linked service to Azure Key Vault. – DEV, UAT & PROD. - Created 3 nodes for DEV and 5 nodes for PROD cluster to migrate data. - Setup and configure Azure Active Directory to provide team access policy for Databricks cluster, Azure Data Factory, Azure SQL, Azure Data Lake house. - Coordinate with TAI Client and Microsoft support team to resolve throughput issues. As Azure & Databricks Data Engineer: - developed most critical data ingestion pipelines using Azure Data Factory (ADF) for E1 to migrate 12.8TB of 120 tables from Db2 to ADLS RAW as a parquet file. There are many large tables with 2-4 TB of volume data containing 400 to 800 million records. - Initial & Incremental migration pipelines for both the E1 and BY sources with a watermark based on Julian's date & time - Design Audit table (Process log) and Control table (System) to achieve dynamic pipeline and audit information for master and child pipeline. - Design architecture solution to achieve delete for PKSNAPSHOT – E1 & BY. - Build dynamic delete pipeline using ADF (load PKTBL), Databricks PySpark for Daily, Weekly, OnDemand, and Yearly frequency to delete records from target (Analytics layer – gold layer) based on source system delete column and delete table - Build transformation using Datarbicks Spark with Scala for E1 to - Apply a transformation with a lookup table and transform to the Silver layer. - Build transformation to transform on Analytics layer (Gold) using Databricks Spark & scala. - Implemented UPSERT using Spark Structure Streaming with 5 minutes on the Analytics layer - Design pipeline architecture for master pipeline, child pipeline with different activity ID, Pipeline ID, Master pipeline ID with different pipeline Run ID to make sure for smooth transition audit. - Build logic, developed using Pyspark on Datarbicks – applied on DEV, UAT & PROD to check counter – master pipeline IN PROGRESS - or NOT so that pipeline execution should not overlap. - Pass pipeline parameter to insert or update Audit/Control table using Databricks -Pyspark. - Monitor Performance in DEV & PROD, worked with the team to reduce time. - Milestone – to achieve 10-minute SLA for Incremental load on E1 & BY (end-to-end completion time) - Milestone – achieved 1.53.45hrs to load (400millions record with2.3TB) at RAW as parquet file using ADF pipeline - Interact with Azure Devos’s engineer to build a CICD pipeline for DEV, UAT & PROD with - Develop pipeline as POC using Databricks Workflow, compare the cost with Azure Pipeline, and present to the client. My Contribution to Past Project: Project: Data Exchange (Security Framework) Roles: Technical Lead & Architect – Confluent KStream & KSQL Client: Fidelity & Westpac Team: 9 members Technical Skills: AzureDevops, Jdk 19.0, Confluent Kafka, Kstream, KSQL, Azure Databricks, DBFS, Delta lake, Azure Data Factory, ADLSGen2, Confluent Schema Registry, AES Algorithm, Hash Algorithm, Kubernetes Cluster(AKS).

With a fervent passion for the intersection of Python, data, and machine learning, I embarked on my journey five years ago after completing my Bachelor's in Computer Science. Armed with a Python certification, I delved into the realm of data-driven insights, immersing myself in the intricacies of Python, SQL, and PySpark. My professional trajectory has been characterized by a steadfast commitment to continuous learning and practical application. Over the past five years, I've honed my skills in Python and its various libraries, leveraging its versatility to tackle a myriad of data challenges. From data manipulation to visualization, Python has been my trusted companion, empowering me to extract actionable insights from complex datasets. In tandem with my Python proficiency, I've delved into the realm of data manipulation and analysis using SQL. Mastering the art of querying databases, I've adeptly navigated through vast troves of data, extracting meaningful patterns and trends to inform decision-making processes. Furthermore, my journey has led me to explore the realm of distributed computing with PySpark. Harnessing the power of parallel processing, I've unlocked new possibilities in data processing and analysis, seamlessly handling large-scale datasets with efficiency and precision. Throughout my professional tenure, I've embraced a dual role, balancing my career with part-time endeavors in software development. This unique blend of academic prowess and real-world experience has enriched my understanding of Python and its applications, fueling my passion for innovation and problem-solving. When it comes to education, I firmly believe in the value of practical, hands-on learning experiences. Hence, I've actively sought out opportunities to engage in practical sessions, applying theoretical concepts to real-world scenarios. This hands-on approach has not only solidified my understanding of Python and machine learning but has also equipped me with the confidence to tackle complex challenges head-on. Driven by a thirst for knowledge, I've pursued online courses to further augment my skill set. From Python fundamentals to advanced machine learning techniques, I've dedicated countless hours to expanding my expertise, investing in courses ranging from one-hour tutorials to comprehensive seven-week programs. Central to my learning journey has been the integration of live sessions, facilitating dynamic interactions and real-time feedback. Whether collaborating with peers or engaging with instructors, these live sessions have fostered a vibrant learning community, enabling me to glean insights and perspectives from diverse sources. As I look towards the future, I am excited to continue my exploration of Python, data, and machine learning. Armed with five years of experience, a robust skill set, and an insatiable appetite for innovation, I am poised to tackle the challenges and opportunities that lie ahead in this dynamic field.

About the Course Duration : 100 hrs (60 hr Python and 20 hr Selenium 20 hr Django) Fee : 8000 Rs/- for online training Fee : 11000 Rs/- for classroom training Benefits: Access to class recordings for 30 days 5 days Free Python Session Live Online or Classroom session Real-time assignments: Finding duplicate files under a multilevel folder Find Cheapest restaurant in a city from a dataset provided Merging excel files Converting Excel file to csv files Inserting data from csv/excel to MySQL database Plot a pie chart to analyse profit from every country to a ecommerce company from a huge dataset available in MySQL Extract telecom data from dataset provided, calculate operator-wise incoming and outgoing call report Python Data Types, methods, built-ins Operators and Control Structures, nested loops Complex Data Structures (Multi-Dimensional) Regular Expressions(Data Extraction and Manipulation) File Handling and Directory modules Functions and advanced functions comprehensions Lambda functions, Generators Closures and Decorators Exceptions Handling Modules and Packages(Writing Real-time package) Object Oriented Python MySQL DataBase Interaction Excel Data Parsing and Writing XML Parsers Serialization using pickle and Json Automation : Automate Server login using SSH WebScraping - Webpage data extraction Python Logger Multi-Threading Numpy Pandas Matplotlib Selenium Web Automation (20 hrs) Django (20 hrs)

I'm a Engineer i have completed my engineering in computer science and i have done my all project including finial year project on python, machine learning and data science so i got interested to make other people also learn and make use of it and i got so many offer but i wanted to teach online only.

I am Working as Machine Learning Developer in Accenture, 4+ years of Experience i am expert in Python,R, julia, DataScience, Machine Learning, Deep Learning, Chatbots, with Different Frameworks such as Tensorflow,Sklearn, Pytorch,NLTK.

I am working in a service-based company from last year in Bangalore. And teaching python, machine learning, deep learning. I am giving home/online/tutor home tuition.

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Mtech from IIT Kharagpur in computer science. Working as a senior software developer for a MNC. I have experience of teaching Gate classes for following subjects ->Algorithms -> Data structures ->Operating Systems C,C++ for around 18 batches Core Java, Spring, Hibernate for around 22 batches Python for around 40 batches

I am having 11 years of Experience of which 2 yrs is on Data Science.I am working as a Architect for reputed software firm.I have completed 3 batches for Python and 1 Batch for Python with Data Science Training.I try to cover simple real time examples and case study in my training.My training is supported by well defined assignment and notes.

Have an 4 years experience with python and django. Generally will provide training in office for our internships . Good explanation skills and try to explore about concepts and deliver to collegues I am interested to share my knowledge to people