Skip to content

styling pages #15

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
Abiola-Zeenat wants to merge 20 commits into
base: jonas
Choose a base branch
from
Open

styling pages #15

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
20 commits
Select commit Hold shift + click to select a range
f88c331
Merge pull request #6 from Dufuna-CodeCamp/jonas
Mirriam6 Mar 21, 2022
43f60db
Merge pull request #7 from Dufuna-CodeCamp/jonas
Edwin-Ngoma Mar 21, 2022
62a3c6d
Data Science modified
Edwin-Ngoma Mar 21, 2022
d8af0ee
Merge pull request #8 from Dufuna-CodeCamp/edwin-Hack
jonasmwansa Mar 21, 2022
bc8f00d
Changes made to the Artificial intelligence page
Edwin-Ngoma Mar 21, 2022
1c53931
Merge pull request #9 from Dufuna-CodeCamp/edwin-Hack
Mirriam6 Mar 21, 2022
dc9f584
added content to Graphics Design Page
Edwin-Ngoma Mar 21, 2022
03d514c
Merge pull request #11 from Dufuna-CodeCamp/edwin-Hack
Mirriam6 Mar 21, 2022
12dd83c
Modified software development page
Edwin-Ngoma Mar 21, 2022
1937742
Merge pull request #12 from Dufuna-CodeCamp/edwin-Hack
Mirriam6 Mar 21, 2022
3f7e91c
updated information Security page
Edwin-Ngoma Mar 21, 2022
72084d0
fixed errors information security
Edwin-Ngoma Mar 22, 2022
b65fb1c
changes made to information security page
Edwin-Ngoma Mar 22, 2022
ab4a125
Merge branch 'main' into edwin-Hack
Edwin-Ngoma Mar 22, 2022
8f36417
Merge pull request #14 from Dufuna-CodeCamp/edwin-Hack
jonasmwansa Mar 22, 2022
92a946d
i added styling to the other html pages
Abiola-Zeenat Mar 22, 2022
ec4f377
added styles
Edwin-Ngoma Mar 22, 2022
e506bc9
Merge pull request #16 from Dufuna-CodeCamp/edwin-Hack
jonasmwansa Mar 22, 2022
cf3fb3a
waitlist linked
Edwin-Ngoma Mar 22, 2022
35ac0a2
Merge pull request #17 from Dufuna-CodeCamp/edwin-Hack
jonasmwansa Mar 22, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
48 changes: 48 additions & 0 deletions css/form-styles.css
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,48 @@

.welcome-remarks{
text-align: center;
margin: 50px;
}

.form{

display:flex;
justify-content: center;
}

form{
background-color: azure;
padding: 20px;
width: 500px;
border: 1px solid slategray;
box-shadow: 1px 2px 10px rgb(8 20 1 / 0.2);
border-radius: 5px;
}

.form input{
width: 70%;
margin-top: 5px;
margin-bottom: 5px;
padding: 5px;
}

.form .button{
display:flex;
justify-content: center;
}

.form button{
margin: 5px;
padding: 5px;
background-color: blue;
border-radius: 5px;
width: 100px;
padding: 5px;
}



button:hover{
cursor: pointer;
background-color:rgba(100, 63, 178, 0.9);
}
16 changes: 14 additions & 2 deletions css/style.css
100644 → 100755
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,3 +1,13 @@
li{
margin-left:60px;
}
p{
margin-left:50px;
margin-right:50px;
}
h1,h2,h3,h4{
text-align: center;
}
body{
font-size: 16px;
font-style: normal;
Expand Down Expand Up @@ -118,19 +128,23 @@ body{
flex: 0 0 32.433333%;
margin: 5px;
height: 550px;
margin-bottom: 20px;
margin-top: 20px;
}

.career-item .career-title{
text-align: center;
font-weight: 700;
padding-bottom: 10px;
}

.career-item img{
height: auto;
width: 70%;
display: block;
margin-left: auto;
margin-right: auto;

}


Expand All @@ -155,8 +169,6 @@ body{
*/




footer{
display:flex;
margin-top: 20px;
Expand Down
243 changes: 243 additions & 0 deletions html/careers/artificial-intelligence.html
View file
Open in desktop

Large diffs are not rendered by default.

228 changes: 228 additions & 0 deletions html/careers/data-science.html
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,228 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>DATA SCIENCE</title>
<!--google fonts-->
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Lato:wght@100;300&family=Poppins:wght@300&family=Source+Code+Pro:wght@200&family=Twinkle+Star&display=swap" rel="stylesheet"> <!--my stylesheet-->
<link rel="stylesheet" href="../../css/style.css" type="text/css">
</head>
<body>
<!--header-->
<div class="header">
<a href="#"><button>Join an Event</button></a>
<a href="#"><button>Talk to an Expert</button></a>
<a href="../../index.html" class="logo">TechGrow</a>
<span class="search">
<input type="search" id="mySearch" name="q" placeholder="Search career path">
<button id="search-btn">Search</button>
<a href="#" class="pull-right"><button>Sign Up</button></a>
<a href="#" class="pull-right"><button>Login</button></a>
</span>
</div>

<!--navigation-->
<nav class="nav navigation">
<a href="../../index.html" class="nav-item nav-link">Home</a>
<a href="../careers.html" class="nav-item nav-link">Careers</a>
<a href="../jobs.html" class="nav-item nav-link">jobs</a>
<a href="../events.html" class="nav-item nav-link">Events</a>
</nav>

<section class="path-description">
<h1>DATA SCIENCE</h1>
<h2>About This Course:</h2>

<div class="content">
<p>
The art of uncovering the insights and trends in data has been around since ancient times.
The ancient Egyptians used census data to increase efficiency in tax collection and they
accurately predicted the flooding of the Nile river every year. Since then, people working
in data science have carved out a unique and distinct field for the work they do. This field
is data science. In this course, we will meet some data science practitioners and we will get
an overview of what data science is today.
</p>
<h2>What is DATA SCIENCE today?</h2>
<p>
Data sciences is an interdisciplinary field that uses scientific methods, processes, algorithms
and systems to extract knowledge and insights from noisy, structured and unstructured data,and
apply knowledge and actionable insights from data across a broad range of application domains.
Data science is related to data mining,machine learning and big data.
</p>
<p>
Data science is a "concept to unify statistics,data analysis,informatics, and their related methods
" in order to "understand and analyze actual phenomena" with data.It uses techniques and theories
drawn from many fields within the context of mathematics,statistics,computer science,information
science, and domain knowledge.However, data science is different from computer science and
information science.Turing Award winner Jim Gray imagined data science as a "fourth paradigm"
of science (empirical,theoretical,computational, and now data-driven) and asserted that "everything
about science is changing because of the impact of information technology" and the data deluge.A data
scientist is someone who creates programming code and combines it with statistical knowledge to create
insights from data
</p>
<h2>How data science is transforming business
</h2>
<P>
Organizations are using data science to turn data into a competitive advantage by refining products and services.
Data science and machine learning use cases include:
</P>
<ul>
<li>
Determine customer churn by analyzing data collected from call centers, so marketing can take action to retain them
</li>
<li>
Improve efficiency by analyzing traffic patterns, weather conditions, and other factors so logistics companies can improve delivery speeds and reduce costs
</li>
<li>
Improve patient diagnoses by analyzing medical test data and reported symptoms so doctors can diagnose diseases earlier and treat them more effectively
</li>

<li>
Optimize the supply chain by predicting when equipment will break down
</li>

<li>
Detect fraud in financial services by recognizing suspicious behaviors and anomalous actions
</li>

<li>
Improve sales by creating recommendations for customers based upon previous purchases
Many companies have made data science a priority and are investing in it heavily. In Gartner’s recent survey of more than 3,000 CIOs, respondents ranked analytics and business intelligence as the top differentiating technology for their organizations. The CIOs surveyed see these technologies as the most strategic for their companies, and are investing accordingly.
</li>
</ul>
<h2>
How data science is conducted
</h2>
<p>
The process of analyzing and acting upon data is iterative rather than linear, but this is how the data science lifecycle typically flows for a data modeling project:
</p>
<p>
<b>Planning:</b> Define a project and its potential outputs.
</p>

<p>
<b>Building a data model:</b>Data scientists often use a variety of open source libraries or in-database tools to build machine learning models. Often, users will want APIs to help with data ingestion, data profiling and visualization, or feature engineering. They will need the
right tools as well as access to the right data and other resources, such as compute power.
</p>
<p>
<b>Evaluating a model:</b> Data scientists must achieve a high percent of accuracy for their models before they can feel confident deploying it. Model evaluation will typically generate a comprehensive suite of evaluation metrics and visualizations to measure model performance against new data, and also rank them over time to enable optimal behavior in production. Model evaluation goes beyond raw performance to take into account expected baseline behavior.
</p>
<p>
<b>Explaining models:</b>Being able to explain the internal mechanics of the results of machine learning models in human terms has not always been possible—but it is becoming increasingly important. Data scientists want automated explanations of the relative weighting and importance of factors that go into generating a prediction, and model-specific explanatory details on model predictions.
</p>

<p><b>Deploying a model:</b> Taking a trained, machine learning model and getting it into the right systems is often a difficult and laborious process. This can be made easier by operationalizing models as scalable and secure APIs, or by using in-database machine learning models.
</p>
<p><b>Monitoring models:</b> Unfortunately, deploying a model isn’t the end of it. Models must always be monitored after deployment to ensure that they are working properly. The data the model was trained on may no longer be relevant for future predictions after a period of time. For example, in fraud detection, criminals are always coming up with new ways to hack accounts.
</p>
</div>

<div class="courses-skills">
<h2>
Courses and Skills Required To Be A Data Scientist
</h2>
<h3>Math:</h3>
<ol>
<li> Calculus</li>
<li> Linear algebra</li>
<li> Probability and Satistics</li>
</ol>

<h3>Programming Languages to know</h3>
<ol>
<li>Python</li>
<li>JavaScript</li>
<li>Java</li>
<li>R</li>
<li>SQL</li>
<li>MATLAB</li>
</ol>

<h3>Summary</h3>
<p>
Summary. Data Science is the area of study that involves extracting insights from vast amounts of data by using various scientific methods, algorithms, and processes. Statistics, Visualization, Deep Learning, Machine Learning are important Data Science concepts.
Anyone with an interest to pursue Data science can become a Data Scientist.
To learn more about this career and find out if its suitable for you please contact us by filling your details in our waitlist Form.
</p>

</div>
<div class="faq">
<h3>FAQ on Data Science</h3>
<h4>1.How can I become a data scientist?</h4>
<p>There are three general steps to becoming a data scientist:</p>
<ol>
<li>
Gain experience in the field you intend to work in (ex: healthcare, physics, business).
</li>
<li>
Earn a bachelor's degree in IT, computer science, math, business, or another related field;
</li>
<li>
Earn a master's degree in data or related field;
</li>
</ol>


<h4>2.What is a Data Science example?</h4>
<ul>
<li>Identification and prediction of disease</li>
<li>Optimizing shipping and logistics routes in real-time, detection of frauds, healthcare recommendations</li>
<li>automating digital ads</li>
</ul>

<h4>
3.Is data science a good career?
</h4>
<p>
Yes, data science is a very good career with tremendous opportunities for advancement in the future. Already, demand is high, salaries are competitive, and the perks are numerous –
which is why Data Scientist has been called “the most promising career” by LinkedIn and the “best
job in America” by Glassdoor.
</p>
<h4>
4.What is the Salary of a Data Scientist?
</h4>
<p>
The average data scientist salary is $100,560, according to the U.S. Bureau of Labor Statistics. The driving factor behind high data science salaries is that organizations are realizing
the power of big data and want to use it to drive smart business decisions.
</p>
</div>
<div class="resources">
<h4>Recommended Articles</h4>
<p>If you want to do further research around the area of Data Science, then these articles will
be of interest to you:
</p>
<ul>
<li>
<a href="https://www.simplilearn.com/tutorials/data-science-tutorial/what-is-data-science">
https://www.simplilearn.com/tutorials/data-science-tutorial/what-is-data-science
</a>
</li>
<li>
<a href="https://www.oracle.com/data-science/what-is-data-science/">
https://www.oracle.com/data-science/what-is-data-science/
</a>
</li>
<li>
<a href="https://www.techtarget.com/searchenterpriseai/definition/data-science/">
https://www.techtarget.com/searchenterpriseai/definition/data-science/"
</a>
</li>
</ul>
</div>
</section>
<footer>
<div class="logo">
<a href="../../index.html">TechGrow</a>
</div>
<div class="useful-links">
<a href="../about.html">About Us</a>
<a href="../about.html">Contact Us</a>
</div>
</footer>
</body>
</html>
Loading