#java database programming assignment and project help

Are you interested in becoming a Java programming expert? Look no further! In this article, we will explore why ACTE Institute is the best online training institute for mastering the Java programming language. Whether you are a beginner or an experienced developer, ACTE Institute offers a comprehensive course that will help you enhance your Java skills and propel your career to new heights.

Why Choose ACTE Institute?

Expert Instructors

ACTE Institute boasts a team of highly skilled and experienced instructors who are passionate about teaching Java programming. They possess a deep understanding of the language and stay updated with the latest advancements in the industry.

Our instructors provide personalized attention to each student, ensuring a conducive learning environment where doubts are addressed, and concepts are clarified.

Comprehensive Course Curriculum

The Java programming course offered by ACTE Institute covers all essential topics, making it suitable for both beginners and those with prior programming experience.

From understanding the basics of Java to advanced concepts like multithreading, exception handling, and Java databases, our course equips you with the knowledge to tackle any Java project with confidence.

Hands-on Learning

This Institute believes in the power of practical learning. Our course emphasizes hands-on coding exercises, real-world examples, and projects that allow you to apply your newly acquired knowledge.

By engaging in practical exercises, you develop a strong foundation in Java programming and gain valuable experience that is essential for success in the industry.

Flexible Learning Options

Everyone has various timetables and learning preferences, and we are aware of this. That's why ACTE Institute offers flexible learning options for its Java programming course.

You can choose between in-person classroom training or convenient online classes, ensuring that you can learn at your own pace and from the comfort of your own home.

Industry-Relevant Projects and Assignments

At the Institute, we believe that practical application is key to mastering any programming language. That's why our course includes industry-relevant projects and assignments.

By working on real-world projects, you gain hands-on experience and develop the problem-solving skills necessary to excel in Java programming.

Placement Assistance

Institute goes beyond just providing excellent training. We also offer placement assistance to our students, helping them kick-start their careers in Java programming.

Our dedicated placement cell connects students with top companies and assists in resume building, interview preparation, and job placement.

hope you’re having a great day too!

What my first year of studying computer science was like

obligatory preface that courses differ between universities and colleges. i study in australia.

The biggest challenge I faced per se going into comp sci was how nothing I did at school prepared me for it. The kind of content I’ve learnt wasn’t similiar to school and the assignments have been very different. No analytical essays and scientific reports for me (there has been essays and reports tho). In my school IT class I learnt basic HTML and CSS which was the only programming knowledge I went into comp sci with. (Id also gotten pretty far on khan academy’s JavaScript course in like year ten but I’ve forgotten all of that now lol).

I have four units a semester and have completed my first year (of 3, although I’m taking less units this year so I’ll finish in 3.5 years).

What I actually did in my first year:

Semester 1 (pre-major picking, two of these were for the other major option)

Learnt general computer hardware and how it functions. The assignment was using a raspberry pi to do something that used hardware (the pi), software (basic code) and the internet (I used twitter). My project is on Twitter at SunsetIFB102

Group project app design stages. Like drawing the layouts, getting feedback, then digital sketches then semi fancy looking sketches (not comp sci major)

Python! I really liked this. Taught the basics of python and in general programming. It was kind of intimidating how many people had coded before so I had to focus on ignoring them and learning for myself. Also really salty I was 1% off a high distinction for the whole unit AGH

Databases and SQL. This would’ve been a useful unit if the lecturer was, how do I put this kindly, good at his job. (Not comp sci major, although definitely use databases later on)

Semester two (all comp sci major)

C# , basics of object oriented programming principles. Which is a fancy way of saying it taught how you should write your code so it’s laid out effectively.

C, how to program microprocessors. Basically how to program hardware machines. C is mostly used for machines like ATMs, a fridge perhaps, probably a roomba and other single purpose kind of things. Also from this I can program arduinos and read arduino code easier since arduino code is a C/C++ hybrid. (This and the previous unit had high fail rates and were honestly Tough)

Information security (apart of network security minor) This unit talked about processes of protecting information in organisations and on a single person level. Basics of cryptography was discussed and hashes and how ways information is kept secure when transferring between objects (like over the internet)

Computation mathematics (apart of intelligent systems minor). This was a weird unit to me and was mostly math majors. It taught all these different equations which allow you to make approximations. Honestly confused how it’s used for computers but we learnt MATLAB and it’s a pre requisite for an intro to robotics unit I’m taking this year :)

So yeah, that’s an account of what I actually studied. Reading over it it seems way more impressive than it probably was. Computer science isn’t easy (well, unless you want to scrape a pass each time) but it isn’t horribly difficult. It’s how different it is to high school work that can trip you up. I can’t make aesthetic studyblr notes on paper because its all on my computer and can’t turn it off when studying because I need it.

My assignments are typically big coding projects, exams (multiple choice if a coding unit) and essays if it deals with theory (like info sec did).

This coming semester I’m learning Java and GUI’s (graphical user interfaces), JavaScript and HTML and whatever else for web applications, and discrete maths which seems to be for notation used later on... it looks very strange.

Hope this helps! If you have any more questions feel free to DM me!

Design parsing methods to extract information from web pages and answer the following questions:

a) Assuming that you live in Toa Payoh town and owns a car. Hence, you are interested to find out what how many carparks are there available in Toa Payoh. Using the data information available, construct a Python program to count the total number of carparks in “Toa Payoh” and the total number of car parks decks available.

b) Assuming that you are driving home to Toa Payoh and hence you are interested to know which of the car parks will provide you the highest chance to getting a lot. Construct another Python program that enable you to check and display in real-time what is the availability of the carparks in Toa Payoh.

c) Based on the results in (a) and (b), how can you improve your program(s) and tabulate your chances of getting a lot in Toa Payoh. You should rank it from highest to lowest chance.

Solution:-

Introduction:

The main aim of this project is to develop a real time avaibility of Singapore's carpark information which can be implemented in Jupyter Python Notebook. The the MySQL database is designed using AWS on the RDS data services. Thus, the analysis of a real time car details will be investigated.Read More

https://www.allhomeworkassignments.com/programming-subjects/python-assignment-help.html Identifies Features That Make Python Unique

With significant measurement in TIOBE programming community index, Python is ranked among the top eight programming languages

It is counted as the third most popular language whose grammatical syntax is not based on the conventional C++, C# and JAVA programming language. Python is highly influenced by C programming language and hence the statement syntax and expressions in C helps the programmer to transit between the two languages. On evaluating the empirical study, Python (scripting languages) are considered to be more productive than C and Java (conventional language).

as with literally everything i write, this got really fucking long! like, wordcounter.net estimates this will take 7 minutes to read. so i’ve placed the bulk of this post under a read more

this is not a quick tips kind of post; this is a detailed breakdown of how to write a resume from scratch, with examples that are largely taken from my own resume. this is primarily a resource for people who don’t know where to start with writing a resume, not for people who just want resume hacks

i’m saying all this so i don’t get people in my inbox complaining about how long this is. writing a resume takes a lot of time and effort, and this post does not shy away from that

creating a resume will take you a while, especially if this is your first attempt. don’t be discouraged! take breaks, and don’t try to make the perfect resume on the first try. this tutorial is designed to be completed in rounds

it usually takes me a week to get a new master resume into working order

don’t worry about page length right now. you should make a multipage master resume that contains every relevant experience before making a 1-page resume. after you’ve made the master, you can build custom resumes from it for job applications

this post is best viewed on desktop, because i use nested bullets, and tumblr mobile hates those

let’s get into it!

step 1:

list out everything you’ve ever done that could feasibly count as a resume entry: extracurriculars, jobs, volunteer positions, research, organizations you were a part of (professional or casual), freelance work, long-term hobbies. i will refer to each different experience as an “entry”

for each entry, write where (city + state) and when (timespan) you did that thing 

ex. tritones a cappella group, los angeles, ca, august 20xx - present

going forward, update this list as you join or complete new jobs/hobbies/whatever so that you don’t have to wrack your brain a year down the road wondering how long you held down that job or leadership role

I think RTFM has its place. I know I’m not in the minority with this view, but it’s not exactly polite to talk about it. We have all started out on the other side of RTFM at some point, clueless and helpless, not knowing where to begin.

To be quite honest, I wasn’t told to RTFM that much, because I learned to program from books when I was 12, and I wished I could ask somebody for guidance. My father still knew BASIC from the late 70s and early 80s, and my teachers knew enough PASCAL to pass their own exams and then teach children how to use Microsoft Excel. There was nobody to turn to.

When I started learning Java from a book, I was very confused, and I learned many bad habits, idiosyncrasies of the book’s author that I stuck with because I didn’t understand what they meant. Then I bought a bigger, heavier book about Java, and I slowly learned to program. I learned programming in general and Java in particular at the same time. One textbook explained what classes in Java do, but not why you would use them, and the other textbook vacillated between treating OOP as a scary newfangled concept nobody understands but everybody has to use because of Java, and something you have to be familiar with already because the book assumed you already knew C, C++, BASIC and smalltalk.

I read the manual and I didn’t understand. What finally got me to understand OOP was ironically learning and reading code in Python. Unlike in Java and smalltalk, OOP in Python is optional. Although everything in Python is an object, the common Pythonic programming style is procedural, with OOP constructs used sparingly when they make sense. This finally let me understand what OOP is good for. No amount of contrived examples like “class PickUpTruck extends Car { ... }“ helped me understand OOP in Java.

The same thing can happen with classes, module systems, macros, build systems, version control systems, bug trackers, databases, and visual modelling languages like UML and FMC. They are all paradigms or technologies to manage complexity, and if I give a student a toy teaching example of a SQL database, multi-module program, or UML diagram, then the student will be confused rather than enlightened. If the complexity is missing from the example, then the benefit of using complexity-mitigating technology is not obvious.

That even goes for comments! What good are comments in a textbook example, with explanatory text already left and right of the code listing?

If I had a teacher who could explain OOP to me, things would have been so much easier. Eventually, I managed to learn what I needed to learn. Some things are much, much harder to learn if you can’t ask a teacher multiple clarificatory question in quick succession. It would be even better if your teacher asked you a couple of questions to drill down on which part you didn’t understand.

Nowadays, I see many questions on Discord, IRC, and forums from people who are just starting out learning to program. It’s a vast difference between learning Unity3D when you are already a programmer who shipped software in C++ and wrote games in Java, and learning programming, C#, game design, level design, shaders, 3D modelling, and the Unity3D Engine in one go.

If somebody asks a confused question online, the first order of business is to establish whether they are an expert or a confused beginner. That can sound confusing and condescending, but I often fear if I give a straight answer to a confused question, I do more harm than good.

When somebody asks “How do I iterate over the pixels in a pygame surface?“, I can give the straight answer, or three advanced answers with different performance characteristics. You probably want to use numPy and cache the results during level loading. Maybe you can also use numPy if it’s only an occasional thing, and you can stomach the dozens of megabytes of native code dependencies. You probably want to use OpenGL with a GLSL fragment shader if you do the thing every frame. If perchance you want to do palette-swaps only, then you can use the pygame palette handing functions rather than iterating over pixels and doing a dict look-up each time. Iterating over all the pixels in a pygame surface is slow. You can probably get away with it on a 16x16 sprite, but not on a 1920x1080 screenshot.

That’s not even the worst of it! I see confused questions by people who think they found a bug in a library/framework/engine, but actually they just don’t understand their own code, or they don’t understand the programming language. I see confused questions by people who don’t know what problem they are actually encountering, who don’t know what to Google.

These people don’t need to be told to RTFM. Either they already read the manual, but they don’t understand it, or they don’t even know which manual, or what to look for. They can’t be told to RTFM, but they can’t be given straight answers either. The best thing you can do is to ask “You’re new to this, aren’t you?“ and point them to a more basic tutorial. Or, if your time is worthless, you can decide to tutor them one-on-one over the Internet.

All these problems can combine into the worst possible scenario: Somebody asks on StackOverflow/IRC/the mailing list/Slack/Discord, because their teacher is not available, or told them to learn to RTFM and figure it out independently. These people can be high school students too intimidated by their teachers to ask questions, university students who can’t be bothered to attend lectures or wait for office hours, or junior programmers who are trying to impress their boss.

Figuring things out is a useful skill to have, but it’s not something you should rely on in a high school class. If you’re a teacher, don’t punish students for asking questions! And don’t expect students to bother strangers on the Internet to do your job for you. The best thing you can do to get students to RTFM is to answer their questions when they get stuck, so they get a good idea of what to look for, which terms to search for, what to ask on IRC.

If you want to teach your pupils to RTFM, you should at least follow up with them and point them in the right direction in case they get stuck trying to look up the answer, or if they don’t understand the text in the manual. Of course you can assign reading, but for some reason, some of your pupils will take this to mean that you refuse to explain the topic, so the only recourse is to ask strangers online.

And then the student comes back next week and asks even more confused questions, now that the next assignment is due, impossible to complete without having understood last week’s topic.

Around a third of confused newbie questions I see are from students who would rather not ask their teachers, not even those who post whole homework assignments.

Some people want us to stop saying RTFM online, ever. They also want us to stop saying “You’re new to this, aren’t you?“ or “Please take a step back and think about what you are trying to accomplish with this“. They all are too condescending. I’m not just trying to shift the blame away from open source projects and programmer online communities. Confused online questions sometimes have offline causes. These causes cannot be hyperlinked, retroactively screenshotted, and posted to twitter.

Despite big data currently ranking among top business intelligence and data analytics trends, businesses continue to suffer from a lack of data-savvy talent. Research from BARC shows half of respondents reporting a lack of analytical or technical know-how for big data analytics. This is good news for tech beginners, however, whose knowledge and skills are being welcomed by companies who want to reap the benefits of big data.

If you find data science a tempting opportunity, you’ll benefit from this overview of big data basics for beginners. Below, we’ll discuss what the requirements for jobs are and which skills you should master in order to start a successful data science career.

What is Big Data?

Instead of reciting a definition or giving a generic overview, let’s look at big data’s key features through the lens of something that is well known to all of us: recommendation engines. These are tools widely used in e-commerce to aid in customer experience, but that also help gather data about consumers. Web store visitors search for products, view them, add and remove them from their carts, make purchases like, etc. – and every activity is an entry in a database. The entry may look like “Customer X opened Product Y page.” Millions of customers exist, and they perform dozens of activities per visit, which means that a retailer needs impressive storage capacity to log all these actions.

Distributed data storage has become a solution to this problem. According to this principle, data is stored on numerous standard computers rather than on one custom-built powerful machine. This allows companies to achieve high scalability: when the number of records increases, the retailer can just add extra machines.

Each time a visitor starts a new tour on the website, the analytical system tracks all their activities and compares them with previous activities of this particular visitor and those of other visitors. In order to perform this task quickly, the analytical system divides the tasks among numerous machines to enable parallel data processing. The analysis results lay the basis for personalized recommendations.

Summing it up: Big data is data sets that resemble a log of events by nature and require distributed data storage, parallel data processing and special approaches and methods. You can learn more about big data use cases in this primer.

Big Data Technology Stack

You should generally expect to master multiple technologies to become an expert in big data. We’ve selected the most popular frameworks and programming languages for a beginner to get acquainted with. The list is not exhaustive: so, feel free to go beyond it whenever you are ready.

Big data frameworks

Apache Hadoop is a framework for parallel data processing and distributed data storage.

Apache Spark is a parallel data processing framework.

Apache Kafka is a stream processing framework.

Apache Cassandra is a distributed NoSQL database management system.

Big data programming languages

Java

Scala

Python

R (not obligatorily, but good to know)

What are the Programming Paradigms Used in Big Data?

It’s advisable to grasp general programming concepts (such as declarative and imperative), as well as big data-specific paradigms (MapReduce).

Declarative paradigm is the approach to programming that is focused on declaring what the task is and the expected results are, without describing the control flow. This approach is used in database programming. For example, SQL (Structured Query Language) is a declarative language.

Imperative programming is the approach focused on describing the commands that should be executed for the program to change its state. It is used for backend development (for instance, in Java).

For example: Copy a directory from A to B shows a declarative approach, while if it’s enriched with such commands as check if there are existing files with the same name and copy only new ones – it’s an imperative approach.

MapReduce paradigm is the concept of parallel processing of distributed data. It allows for dealing with large data sets by applying map function for data filtering, sorting or parameterization and reduce function for summarizing the interim results.

Jobs in Big Data

Now for the burning question: What kinds of big data jobs exist? The good news: there is quite a choice.

Data analysts closely interact with the end users to identify their needs, analyze and interpret data, build reports and visualize data.

Data scientists assess data sources and establish data collection procedures, apply algorithms and machine-learning techniques to mine data.

Data architects design databases and develop relevant documentation and policies.

Database managers control database performance, troubleshoot the corporate databases and upgrade hardware and software.

Big data engineers design, implement and support big data solutions.

Don’t be misled by the fact that only one of the jobs – a big data engineer – refers to big data directly. With good knowledge of big data, you have more value for any job in data analytics. With the lack of such knowledge, you may have limited opportunities in terms of the tasks or projects assigned.

Hi Katja, let me ask about your professional experience: how did you find your interest in computational linguistics and developed through it?

Hi, I started my university studies in Rostov-on-Don, Russia. My subject was German language and literature, with emphasis on literature and translation studies. I studied for 2 years and then continued my studies at the University of Cologne in Germany. I started there from the first year, as in Germany similar program starts two years later than in Russia. Additionally, I took another topic of interest, French, as I was keen to learn it. But after a couple of years, I realized I had high interest in linguistics, especially after taking courses in modern linguistics and formal syntax in university. But honestly, I was not aware of computational linguistics at that point. One day I found that there is a study subject ‘Linguistic data processing’ at the University of Cologne and I joined the class after a talk with a professor. After a couple of years I started to work at the department, and of course, it was a good time to learn programming, which I really enjoyed. At that point, I realized much more about computer science. We studied Java as a first language, though many in the field start now with Python. I remember we programmed a search engine over a summer.

It reminds me a talk to Natalia Karlova-Burbonus. Natalia has a very similar story: going from interest to the German language to Computational Linguistics in Germany. 

My next question whether you remember your first project or last at that time.