Towards AI

SEPTEMBER 28, 2023

PySpark is an interface for Apache Spark in Python. With PySpark, you can write Python and SQL-like commands to manipulate and analyze data in a distributed processing environment. It leverages Apache Hadoop for both storage and processing. It does in-memory computations to analyze data in real-time.

Apache Hadoop 73

Apache Hadoop Hadoop Python SQL 73

Data Science Dojo

JULY 7, 2023

In essence, coding is the process of using a language that a computer can understand to develop software, apps, websites, and more. The variety of programming languages, including Python, Java, JavaScript, and C++, cater to different project needs. Each has its niche, from web development to systems programming.

Data Science 195

Data Science Data Scientist Decision Trees Python 195

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

MAY 31, 2023

Python is one of the widely used programming languages in the world having its own significance and benefits. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science. Some of the top Data Science courses for Kids with Python have been mentioned in this blog for you.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

JULY 18, 2023

Python: Versatile and Robust Python is one of the future programming languages for Data Science. However, with libraries like NumPy, Pandas, and Matplotlib, Python offers robust tools for data manipulation, analysis, and visualization. Enrol Now: Python Certification Training Data Science Course 2.

Data Science 52

Data Science SQL Data Scientist Apache Hadoop 52

Dataconomy

JULY 24, 2023

Programming skills A proficient data scientist should have strong programming skills, typically in Python or R, which are the most commonly used languages in the field. There are numerous online platforms offering free or low-cost courses in mathematics, statistics, and relevant programming languages such as Python, R, and SQL.

Data Scientist 172

Data Scientist Data Analyst Data Science Machine Learning 172

Smart Data Collective

OCTOBER 14, 2019

With big data careers in high demand, the required skillsets will include: Apache Hadoop. Software businesses are using Hadoop clusters on a more regular basis now. Apache Hadoop develops open-source software and lets developers process large amounts of data across different computers by using simple models. NoSQL and SQL.

Big Data 75

Big Data Big Data Apache Hadoop Hadoop 75

Mlearning.ai

MAY 23, 2023

Mathematics for Machine Learning and Data Science Specialization Proficiency in Programming Data scientists need to be skilled in programming languages commonly used in data science, such as Python or R. Familiarity with libraries like pandas, NumPy, and SQL for data handling is important.

Data Science 52

Data Science Data Scientist Apache Hadoop Machine Learning 52

Pickl AI

MARCH 24, 2023

Effectively, Data Science Bootcamps help you learn various languages important in Data Science like Python, Python Libraries, Hadoop, R, SQL and Spark. Accordingly, some of these benefits include the following: It teaches you to learn various languages like Python, Pandas, Java, Scala, Hadoop, SQP, R, etc.

Data Science 52

Data Science Data Scientist Data Analysis Data Analysis 52

Pickl AI

AUGUST 1, 2023

Python for Data Analysis by Wes McKinney Focused on using Python for data manipulation, analysis, and visualization, this book is ideal for aspiring Data Engineers. Key Benefits & Takeaways: Master Python’s data processing capabilities, making you proficient in data cleaning, wrangling, and exploration.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Strong programming language skills in at least one of the languages like Python, Java, R, or Scala. Hands-on experience working with SQLDW and SQL-DB. Knowledge in using Azure Data Factory Volume. What is Polybase?

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

Pickl AI

FEBRUARY 28, 2023

Furthermore, they must be highly efficient in programming languages like Python or R and have data visualization tools and database expertise. Effectively, Data Analysts use other tools like SQL, R or Python, Excel, etc., At length, use Hadoop, Spark, and tools like Pig and Hive to develop big data infrastructures.

Data Analyst 52

Data Analyst Data Scientist Data Science Computer Science 52

Mlearning.ai

MARCH 15, 2023

Technical requirements for a Data Scientist High expertise in programming either in R or Python, or both. Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Knowledge of big data platforms like; Hadoop and Apache Spark. Basic programming knowledge in R or Python.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

ODSC - Open Data Science

APRIL 26, 2023

Though scripted languages such as R and Python are at the top of the list of required skills for a data analyst, Excel is still one of the most important tools to be used. Because they are the most likely to communicate data insights, they’ll also need to know SQL, and visualization tools such as Power BI and Tableau as well.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Dataconomy

JULY 25, 2023

Data scientists use a combination of programming languages (Python, R, etc.), Here is why: Skill and knowledge requirements: Data science is a multidisciplinary field that demands proficiency in statistics, programming languages (such as Python or R), machine learning algorithms, data visualization, and domain expertise.

Data Science 91

Data Science Data Scientist Machine Learning Machine Learning 91

IBM Journey to AI blog

SEPTEMBER 19, 2023

Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala. And you should have experience working with big data platforms such as Hadoop or Apache Spark. To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI.

Data Science 84

Data Science Analytics Analytics Data Scientist 84

Data Science 101

JUNE 10, 2019

Hadoop, SQL, Python, R, Excel are some of the tools you’ll need to be familiar using. Among the skills necessary to become a data scientist include an analytical mindset, mathematics, data visualization, and business knowledge, just to name a few. Each tool plays a different role in the data science process.

Data Science 96

Data Science Data Scientist Data Analyst Data Engineering 96

phData

AUGUST 9, 2023

Open source big data tools like Hadoop were experimented with – these could land data into a repository first before transformation. All while having an extremely low barrier to entry, only requiring SQL to begin to get comfortable, and a Pythonic templating engine known as Jinja allows you to template and automate various models.

ETL 52

ETL Data Warehouse Cloud Data Big Data 52

O'Reilly Media

SEPTEMBER 15, 2021

When we looked at the most popular programming languages for data and AI practitioners, we didn’t see any surprises: Python was dominant (61%), followed by SQL (54%), JavaScript (32%), HTML (29%), Bash (29%), Java (24%), and R (20%). Change in salary for women and men over three years. Salaries by Programming Language.

AI 145

AI AI Azure AWS 145

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

IBM Journey to AI blog

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. Python is the most common programming language used in machine learning.

Machine Learning 59

Machine Learning Machine Learning Data Science Big Data 59

Analytics Vidhya

JANUARY 2, 2023

Introduction You must have noticed the personalization happening in the digital world, from personalized Youtube videos to canny ad recommendations on Instagram. While not all of us are tech enthusiasts, we all have a fair knowledge of how Data Science works in our day-to-day lives. All of this is based on Data Science which is […].

Data Engineering 291

Data Engineering Data Engineer Data Engineering Data Engineering 291

Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Knowledge is power. Sharing knowledge is the key to unlocking that power.”― Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon.

Data Science 273

Data Science Analytics Analytics Apache Hadoop 273

Smart Data Collective

MAY 20, 2019

For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. SQL programming skills, specific tool experience — Tableau for example — and problem-solving are just a handful of examples. Data processing is another skill vital to staying relevant in the analytics field.

Analytics 111

Analytics Analytics Data Analyst Machine Learning 111

Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? If all of these describe you, then this Blogathon announcement is for you! Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […].

Data Science 269

Data Science Analytics Analytics Hadoop 269

Pickl AI

JULY 24, 2023

Skills Required for Data Science To excel in the field of data science, several key skills are essential: Proficiency in programming languages such as Python, R, or SQL Strong statistical knowledge and understanding of mathematical concepts Data manipulation and visualization skills using tools like Pandas, NumPy, and Tableau Machine learning algorithms (..)

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20. The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya.

Machine Learning 400

Machine Learning Machine Learning Data Science Analytics 400

The MLOps Blog

JANUARY 23, 2023

More useful resources about DVC: Versioning data and models Data version control with Python and DVC DVCorg YouTube DVC data version control cheatsheet At this point, one question arises; why use DVC instead of Git? It has Git semantics, including features for cloning, branching, merging, pushing, and pulling.

ML 52

ML ML Data Lakes Machine Learning 52

Data Science Dojo

JULY 24, 2023

Hadoop Distributed File System (HDFS) : HDFS is a distributed file system designed to store vast amounts of data across multiple nodes in a Hadoop cluster. Example Python code snippet using MapReduce: Apache Spark Apache Spark is an open-source distributed computing system that provides an alternative to the MapReduce model.

Big Data 195

Big Data Big Data Data Engineering Data Engineer 195

Smart Data Collective

NOVEMBER 8, 2020

Data engineering primarily revolves around two coding languages, Python and Scala. You should learn how to write Python scripts and create software. As such, you should find good learning courses to understand the basics or advance your knowledge of Python. As such, you should begin by learning the basics of SQL.

Data Engineering 82

Data Engineering Data Engineer Data Engineering Data Engineering 82

Analytics Vidhya

MAY 21, 2023

Introduction Not a single day passes without us getting to hear the word “data.” It is almost as if our lives revolve around it. Don’t they? With something so profound in daily life, there should be an entire domain handling and utilizing it. This is precisely what happens in data analytics.

Analytics 318

Analytics Analytics Power BI Hadoop 318

phData

SEPTEMBER 20, 2023

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. On the server side, runtimes include Python, Java, and Scala in the warehouse model or Snowpark Container Services (private preview). Why Does Snowpark Matter?

SQL 98

SQL Python Data Lakes Machine Learning 98

Pickl AI

APRIL 2, 2024

Tools and Technologies Python/R: Popular programming languages for data analysis and machine learning. SQL (Structured Query Language): Language for managing and querying relational databases. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52