This program provides the knowledge and hands-on experience you need to succeed in the ever-evolving data-driven world.
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Get Complete Hands-on Practical Learning Experience through Assignments, Quizzes & Real-World Projects for Proper Confidence Building
Get 1-1 Personal Chat Support for Doubt Clearance everyday between 6PM to 12PM (including weekends also). Also between 8PM to 9PM daily, you can resolve your doubts over Live Zoom Meeting from our Teaching Assistants.
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Python is the backbone of Data Science. It is the most widely used language for DE. It’s very easy to learn compared to other languages and non-tech people can also learn it. You need not become an expert in it. You should mainly know how to manipulate data using it.
SQL is the most underrated skill of a Data Engineer. It is used to pull required data points from the complex database of clients. You need to write long queries using joins to get the relevant data points.
Statistics is what makes Data Science unique. Lots of Data Science problems are solved using statistics tests. Also understanding the dataset is done using statistics. It is very important for interviews.
Tableau is a software that offers collaborative data visualization for organizations working with business information analytics. In this course we have covered tableau from basics to advance which will help any individual to clear data analyst interviews.
Microsoft Power BI is a business intelligence platform that provides nontechnical business users with tools for aggregating, analyzing, visualizing and sharing data. In our course we have covered all aspects of powerbi necessary to clear data analyst interviews with different case studies to showcase in your resume.
Excel is a spreadsheet program from Microsoft and a component of its Office product group for business applications. Microsoft Excel enables users to format, organize and calculate data in a spreadsheet. Its features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).
If you are starting going to start your career in Data Domain then you must have understand of this domain completely. In this section you will get the complete overview of the data science domain and its different key components.
Machine learning is core of Data Science. These are mathematical algorithms which try to find patterns and relationships in the input and output of the given dataset. You need to know the inner workings of the algorithms and also how to do hyper parameter tuning.
Deep Learning is a subset of Machine learning. It deals with neural networks which solves complex problems of Computer Vision, Natural Language Processing and time series predictions. Someone will to target advance Data Science roles must have this skill.
Amazon QuickSight allows everyone in the organization to understand data by asking questions in natural language, exploring through interactive dashboards, or automatically looking for patterns and outliers powered by machine learning. It is also an add on tool for resume and shows your desire for learning.
Data Studio is a free tool that turns your data into informative, easy to read, easy to share, and fully customizable dashboards and reports. It is not a necessary tool for you but it's good to add extra tool in your resume to show your fire for learning. It can be helpful if your company decides to use this tool for data analysis.
DSA is not a prime necessity of Data Science but some companies do ask DSA related questions specifically the product based companies like Amazon
Generative artificial intelligence (AI) describes algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and videos.
R is not widely used as compared to Python but still some companies use it. It’s very power when it comes to plotting variety of graphics. The Exploratory Data Analysis is done better with R as compared to python.
Kaggle is a good place to participate in machine learning/ deep learning competitions. This course covers about kaggle platform and how you can utilise kaggle to build your portfolio. It explains how you can use dataset, notebooks, competition here to get medals and boost your portfolio.
Enter in the dimension of Big data with this module. Hadoop is a framework for processing and storing massive datasets across distributed systems. This module covers Hadoop's evolution, HDFS architecture, its ecosystem, and essential Linux and HDFS commands.
MapReduce is a programming model for processing large-scale data on Hadoop. Topics include its phases, combiners, partitioners, hash functions, and practical use cases.
Hive is a data warehouse tool on Hadoop that uses a SQL-like language for querying and managing large datasets. Key topics include Hive architecture, built-in functions, partitioning, bucketing, and file formats.
Sqoop is a tool designed for efficiently transferring bulk data between Hadoop and relational databases. It supports import/export, connecting to databases like MySQL, and incremental data updates.
HBase is a scalable NoSQL database on Hadoop for real-time processing. It supports distributed storage, schema-less design, and comparisons with traditional databases like RDBMS and Cassandra.
Scala is a powerful programming language that combines functional and object-oriented programming. It supports advanced features like type systems, recursion, collections, and functional programming constructs.
Apache Spark is a powerful, open-source distributed computing system for big data processing. This module covers concepts like RDDs, DAG, Spark SQL, data handling, aggregations, joins, Spark optimization, and Spark Streaming. It also explores comparisons with MapReduce and Spark's execution on Yarn.
PySpark is the Python API for Apache Spark, enabling scalable data processing and machine learning. This module covers distributed data handling, transformations, actions, Spark SQL, dataframes, machine learning pipelines, and streaming analytics, making it a powerful tool for big data processing with Python.
Apache Kafka is a distributed event-streaming platform designed for high-throughput, fault-tolerant messaging. This module covers topics like Kafka architecture, producers, consumers, brokers, topics, partitions, and real-time data processing, making it essential for building robust data pipelines.
Apache Airflow is a platform to programmatically author, schedule, and monitor workflows. This module covers Airflow architecture, installation, creating DAGs, cron job creation, log viewing, and sensor usage.
AWS is a comprehensive cloud platform offering scalable computing and storage solutions. This module explores services like S3, EC2, Athena, Glue, Redshift, Elastic IP, and storage solutions like EBS, along with comparisons like HDFS vs. S3 and on-prem vs. cloud.
Azure Databricks is a collaborative, cloud-based big data and AI platform. This module includes Databricks architecture, workspace assets, DBFS, data utilities, creating mount points, and integrating Azure Blob Storage and ADLS Gen2 using account keys or SAS tokens.
Snowflake is a cloud-based data warehousing platform known for its scalability and performance. This module covers architecture, loading structured and unstructured data, Snowpipe, zero-copy cloning, data sharing, performance optimization, and advanced features like Time Travel and Fail Safe.
Google Cloud Platform offers scalable cloud computing solutions. This module focuses on GCP fundamentals, BigQuery for data analytics, and Pub/Sub for real-time messaging and data streaming. Pub/sub
Machine Learning & Deep Learning Projects are essential to showcase in your resume to reflect the learnings of your skillset. These projects will have the same level of detailed work as required in an actual company project. That's why we have selected different problem statements from computer vision, NLP and time series which you can work on to excel in Deep Learning.
Data analytics projects are important for businesses and organizations as they enable the collection, analysis, and application of data-driven insights for informed decision-making, process optimization, and improved performance.
A data pipeline is the art of designing and building systems for collecting storing and analyzing data at scale. Organisations have the ability to collect massive amounts of data and they need the right people and technology to collect this huge amount of data so it is in a highly usable state by the time it reaches data scientists and analysts.
In this section, we will be building end-to-end data pipelines using the big data tech stack that we have learnt in the course
The LinkedIn Growth course teaches users how to build a strong and effective LinkedIn profile, grow their professional network, and use LinkedIn to find new career opportunities. The course covers a range of topics, including profile optimization, content creation, network building, and job search strategies, and is designed to help users improve their visibility and influence on the platform.
This course teaches you how to create a strong and effective resume that highlights your skills and experience, and how to tailor your resume to specific job postings. The course covers a range of topics, including resume formatting, keyword optimization, and cover letter writing, and is designed to help you stand out from other applicants in a competitive job market.
You will be learning about other online job portals hack that will increase your chances to getting call for interviews. It covers Naukri, AngelList, Hirect etc
The HR Round Interview QnA course can help you improve your chances of success. This online learning program covers a range of common interview questions and provides tips on how to answer them effectively. The course also includes information on how to prepare for an interview, how to make a positive first impression, and how to follow up after the interview.
Some companies keep first round as aptitude to check thinking skills. In this course we have covered aptitude topics with their examples which are widely asked in aptitude round of interviews. This course is divided into Quantitative, logical and verbal aptitude sections. It will help learners to build logic on all 3 levels of aptitude.
You will get recorded Interview Mock Sessions that will help you to understand the Interview Process and question types. It covers Python, SQL, Machine Learning, Statistics etc Mock Interview Session and we keep updating it.
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I have transitioned my career from Manual Tester to Data Scientist by upskilling myself on my own from various online resources and doing lots of Hands-on practice. For internal switch I sent around 150 mails to different project managers, interviewed in 20 and got selected in 10 projects.When it came to changing company I put papers with NO offers in hand. And in the notice period I struggled to get a job. First 2 months were very difficult but in the last month things started changing miraculously.I attended 40+ interviews in span of 3 months with the help of Naukri and LinkedIn profile Optimizations and got offer by 8 companies.
Based on my career transition and industrial experience, I have designed this course so anyone from any background can learn Data Science and become Job-Ready at affordable price.
Data Scientist @IBM | ex-TCS
Data Engineer @ ADI || MTech (CSE) @ IIT Bhubaneswar || Ex-Research Intern @IIT KGP
Data Scientist @ Karza Technologies
Data Scientist @ HSBC
Software Engineer (Machine Learning) @ Teradata
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⦿ We provide complete hands-on practical learning experience to our learners which we are doing through our structured tutorial videos and most importantly Assignment & Projects Driven Courses that you will not get anywhere.
⦿ Our vision is to provide courses are Most Affordable Price so anyone from any background can learn from it. Nowhere you will get such valuable contents and features in a single course at such price.
⦿ We provide 1-1 Chat Support for Doubt Clearance daily so learners can study smoothly and fast. Other institutes provide support over Email or provide only online community based support which is not that much beneficial.
⦿ We provide lifetime course content access and it is a self-paced course as well so anyone can learn according to their time and manager their work and study.
⦿ We keep tracking our learners progress and also connect with them over Call/Chat to guide them and help them to achieve their goals.
This course has been designed keeping beginners in mind. You will be able to learn as we start from basics. We have many learners doing this course who had no prior coding experience.
In fact, 30% of our Data Science & Analytics Course learners are from non-coding background like mechanical, civil, commerce, arts, MBA, BCA, bio-tech, etc and they are getting jobs and other benefits after completing this course.
In this Data Engineering Course, you will get the same vibes and support from our team and you will become job-ready after your course completion.
Yes, CloudyMl's Matrix cover everything provided by CloudyML. It is a combination of our Data Science & Analytics Program and Data Engineering Progam.
After completing this course, you will become job-ready for the roles like Data Scientist, Data Analyst, Business Analyst, Data Engineer, ML Engineer, Research Analyst etc.
In general, it may take around 7-8 Months to complete the entire course if you give 2-3 Hours per day. It is a Self-Paced course with lifetime access, you can learn according to your time. You can learn different parts of this course and become job-ready for different data roles. You will get complete access to the course content and you can learn according to your preferance also.
The course is designed in the form of Videos & Assignments. In Assignments we have topic wise tutorial video links followed by related questions. You are supposed to code the solutions.
If you are stuck somewhere then you can reach to our Teaching Assistant. They are available from 6P.M to 9A.M. everyday on App Chat or Web Chat. Also 8-9PM Live Doubt Session over Zoom you will be getting. After completion you need to submit the assignment and you will receive the solution file.
No, the Matrix Program focuses on equipping learners with comprehensive skills in data science, analytics, and engineering, ensuring you are industry-ready. While it does not include direct placement assistance, it features essential modules such as General Aptitude and Job Hunting Techniques. These modules are specifically designed to help you understand the job market, refine your job-hunting strategies, and improve your chances of securing the right opportunity.
For those seeking dedicated placement guidance, we offer a specialized course that focuses on preparing you for job applications, mastering interviews, and achieving career success. [Click Here To Check]
We will assign you Experienced Data Scientists and Engineers from our team who will resolve all of your doubts and queries within 10-20 mins. They will be available everyday between 6pm to 12 midinght to resolve your queries over chat.
You will get dedicated 6 hours of personal chat support for your doubt clearance. On the app chat, you can sent Text Messages, Images, Voice Recording, Videos and files and your Teachning Assistant will guide you and resolve your doubts within 10-20 mins. This support will be available everyday and comes with lifetime access so you can chat after your course completion as well.
You will get Lifetime access to the entire course including videos, assignments, projects etc.
It’s one time payment and you will get lifetime access to this course experience.
While making the payment, you will be also creating your account in our learning portal. Just after your payment your course will be added to your account and you can start your learning journey instantly
We do not have refund policy. Please visit our page for more details
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