This repo is to add pages on various career paths and roadmaps such as data scientist, software engineer etc.

Draft Data Scientist career path by the Government Data Science Partnership

This repository is for completed projects and code snippets from Codecademy Data Scientist: Analytics Specialist Career Path: https://www.codecademy.com/learn/paths/data-analyst

Tech career has taken over the world with an exponential increase in opportunities in the job market. Niche fields like data science and cybersecurity are booming with hefty salary packages. Every industry in the world is facing some technological disruption degree but, Information Technology is a diverse industry that can take careers in n number of directions. Which career path to follow in the world is not an easy determination? Here are the top 10 tech careers in Australia that are booming and taking off now, according to the Asia-Pacific Tech and Executive Talent Specialists Findings. Java, Python & GoLang Developers Their primary platforms work well with algorithms required to operate or build AI functionalities and Machine Learning. So they are in current top trends now. Experts in these are difficult to find by as the experience is mostly coming from the startup space, not from the larger employers. JavaScript Developers (with Angular or React Expertise) JavaScript Developers are among the top 10 tech careers in Australia. It’s a versatile language used across a variety of businesses so will continue to be in demand for their talents. The larger number of frameworks within the language makes it a talent pool segmented across niche expertise. DevOps (Cloud) & DevSecOps (Security) & Cloud Security Engineers These are required to maintain and automate the developer’s environment. It’s growing as businesses are becoming more reliant on high volumes of data. DevOps engineers speed up the deployment rate and ensure the minimal downtime of products. DevSecOps Engineers perform same with a focus on security code level security. Cloud Security Engineers instruct on maintaining the quality of coding methods which promote a secure cloud-based environment. Cyber Threat Intelligence / Cyber Emergency Response (CERT) Managers These specialists act as a bullet in the world of cyber attackers. They identify and mitigate risk and respond to cyber-attacks allowing businesses to maintain service, productivity, and data security. Automation Engineers They speed up the market and reallocate the resources by automating human capital savings and processes saving cost. Data Scientists These jobs are booming as businesses seek to better understand and derive value from the data they have generated from their customers. More enterprises are consequently turning to data scientists to apply data-driven strategy decisions and allocate resources more efficiently for a better forecast. Data Engineers They are the critical members for an enterprise as a data analytics team. Their demand is high as more and more businesses are becoming reliant on manipulation and collection of high volumes of data. Agile Coaches / Scrum Masters They are responsible for teaching and running methodological processes and frameworks in the search for efficiency. So demand for these roles will continue to grow. CX/UX Researchers and Designers They are responsible for collecting and making design decisions based on customer experience data and allow the businesses to create better efficiencies across the organization by optimizing their product to something that serves the requirements of the customers. Tech Sales Executives (Enterprise Level) Enterprise-level Tech Sales Executives will always be in demand as they are responsible for an efficient path towards the capital growth of the business. The salesperson who can build strong relationships and grow steadily are in constant demand.

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From Code Academy's Data Scientist career path (EddisFargo's solution)

A repo containing a project done as part of the Data Scientist Career Path on Codeacademy.

Code for CodeAcademy's US Medical Insurance Portfolio Project as part of the Data Scientist Career Path

This is a very basic insurance calculator project that I created with the help of the data scientist career path on Codecademy.

This is a very basic insurance calculator project which focuses on using functions that I created with the help of the data scientist career path on Codecademy.

This repository contains my solutions to the projects in the Codecademy Data Scientist: Natural Language Processing Career Path, completed in Jupyter notebooks. The projects include Python Fundamentals, Linear Regression, and more, and are provided as a reference and for learning purposes only.

Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy! We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning: Programming with Python NumPy with Python Using pandas Data Frames to solve complex tasks Use pandas to handle Excel Files Web scraping with python Connect Python to SQL Use matplotlib and seaborn for data visualizations Use plotly for interactive visualizations Machine Learning with SciKit Learn, including: Linear Regression K Nearest Neighbors K Means Clustering Decision Trees Random Forests Natural Language Processing Neural Nets and Deep Learning Support Vector Machines and much, much more! Enroll in the course and become a data scientist today! Wat zijn de vereisten? Some programming experience Admin permissions to download files Wat leer ik in deze cursus? Use Python for Data Science and Machine Learning Use Spark for Big Data Analysis Implement Machine Learning Algorithms Learn to use NumPy for Numerical Data Learn to use Pandas for Data Analysis Learn to use Matplotlib for Python Plotting Learn to use Seaborn for statistical plots Use Plotly for interactive dynamic visualizations Use SciKit-Learn for Machine Learning Tasks K-Means Clustering Logistic Regression Linear Regression Random Forest and Decision Trees Natural Language Processing and Spam Filters Neural Networks Support Vector Machines Wie is het doelpubliek? This course is meant for people with at least some programming experience

Big data and analytics play a key role as organizations begin their digital transformation journey. Enterprises across industries such as manufacturing, retail, banking, and telco are looking for advanced predictive analytics solutions to better manage machinery, fraud cases, customer satisfaction, and customer expectations. Organizations in Malaysia have started to prioritize analytics solutions to make strategic decisions in their business processes. Currently, there is an increasing amount of unstructured data gathered from various channels such as social media, company websites and contact centers by enterprises in Malaysia. Enterprises are tapping into these internal resources and are inclined to use analytics to analyze these data to create useful information. Visual analytics, which has great potential to impact business processes, are taking the lead in Malaysia because of its functionalities to support the analytic workflow, provide immediate access to readily consume analytics, and enable non-IT staff to analyze, visualize, share, and review data. Big data and analytics are no longer uncommon in Malaysia, and many organizations have started to accept this technology these days. By using analytic capabilities, organizations will be able to run its business operations, improve the overall customer experience, and expand its product and services offering, by increasing their competitive advantage over other existing competitors in the market. Software vendors and its channel ecosystem play an important role in driving the adoption of big data technology among enterprises of various sizes and industries in Malaysia. Some local banks and hospitals have adopted IBM Watson into their organization to improve customer services in the banking sector and provide medical assistance to doctors for cancer treatment in the healthcare sector respectively. As data is now the new business currency and the key to the growth for enterprises, there will be an increase in the need for customization, options for deployment method, consultation, and incorporation of cognitive computing capabilities in software solution offerings to guide enterprises in their big data technology adoption journey. Big Data Analytics [BDA] is no longer a futuristic abstract concept but is something that is already happening today. In an increasingly hyper-connected world, the possibilities of big data continue to evolve rapidly to grab the vast opportunities that BDA has to offer. With the implementation of the big data analytics solutions, governments, businesses and the people can gain much-needed feedback and precious insights that can tremendously improve the decision-making process. Digital Malaysia has identified big data as a major catalytic area to drive these results. The quantitative study aspires to discuss various issues related to big data analytics by tracing the research trends in Malaysia. The data science certification course is well suited for the participants at all levels of experience, by creating an increase in demand for skilled data scientists. This course is best suited for: Professionals in IT, looking for a change in career into data analytics, Software developers, looking for a change in career into data analytics, Professionals who are already working in business intelligence & reporting, Mathematicians, statisticians and economists, Six Sigma consultants, who have statistics exposure, Graduates looking to build a career path in analytics and data science and Anyone who have genuine interest in the business analytics. There are no prerequisites for this training course. This is the best course to start with if you are new in the field of data science.

I am a proactive person who believes that a strong dedication towards quality work and professional attitude brings success to the work industry. Critical thinking, passion, and dedication are my framework for success. My ambition is to provide fresh perspectives and trying new techniques that will help the company evolve. On my career path I want to grow a career as Software Developer and Data Scientist where I would implement new skills while providing high ethical standards to the field of work. I thrive in environments where I am able to make a direct impact utilizing analytical thinking skills and complex problem-solving to find solutions and achieve results. I pride myself in possessing and having demonstrated good interpersonal skills including; communication, collaboration, planning. Throughout my past experience in Data engineering, I have gained working proficiency in the following tools: SQL, R, Power BI, Machine learning, Tableau, SAS, SPSS, Excel and Python I now have the knowledge of; Analyzing local, national, and global trends that impact both the organization and the industry using statistical tools/Machine learning in a complex datasets to prepare reports for the management that could be helpful for the diagnosis and prediction to assess business performance over periods of time. Throughout my academic year I manage to work with C# (build web apps that can be supported with Windows servers) and MySQL to build web development. Lastly I am an honest person that's eager to learn.

Data Scientist Career Path

career path - data scientist

How to level up as a data scientist

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for data scientist career path

Data Scientist Career Path - Codecademy

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Data Scientist Career Paths | Codecademy

This are all the projects I did on the Data Scientist with Python Career Track

This repository contains all the challenges projects I've been doing in my Data Scientist Career on codecademy Path courses.

Codecademys Data Scientist: Analytics Career Path

Learning path of Data Camp: Data Scientist by Python career path.

Data Scientist: Machine Learning Specialist Career Path - Branch for Projects in Career Path

Project in Data Scientist career path with Codecademy.

For this project, I will be investigating a medical insurance costs dataset in a .csv file using the Python skills developed do far in Codecademy Data Science Career Path. In the project I will use classes, for loops and only the csv library.

Projects from "Assosiate Data Scientist" career path in Datacamp