The Powerful Packages for Problem Solving bundle is a fast-paced, hands-on learning path designed to launch your career in Data Science and Predictive Analytics. This course is perfect for beginners with basic Python knowledge who want a quick, practical introduction to solving real-world problems using industry-standard tools.

In today's market, the ability to rapidly analyze data and build predictive models is a highly valued skill. This bundle will quickly get you up to speed with the most important components of the Anaconda distribution, teaching you how to effectively use Jupyter Notebooks and essential Python libraries to perform end-to-end data analysis.

Key Skills You Will Master:

Jupyter Notebooks and Fundamentals: Master the basic and useful features of Jupyter, turning it into your primary environment for data experimentation and reporting.
Exploratory Data Analysis (EDA): Learn to identify investigation areas and perform the initial analysis required to understand and prepare any dataset.
Machine Learning Classification: Understand how to plan a machine learning strategy, train multiple classification models, and apply essential techniques like K-Fold Cross-Validation.
Model Tuning and Enhancement: Utilize validation curves and dimensionality reduction techniques to fine-tune your predictive models for maximum accuracy and performance.
Web Scraping and Data Gathering: Acquire the crucial skill of gathering your own data by scraping tabular data from open web pages and transforming it into powerful Pandas DataFrames.
Interactive Visualization: Finish the data science pipeline by creating interactive, web-friendly visualizations to clearly and effectively communicate your analytical findings to stakeholders.

This course provides the core, actionable skills required for entry-level Data Science roles. By mastering these powerful Python packages and the practical problem-solving workflow, you will gain the confidence and exposure needed to analyze real-world datasets and immediately contribute to analytical projects.

Unlock the power of Python for Data Science. Enroll now and start building your predictive models today!

Also Included - 4 Courses: An Essential Career Skills Pack with 4 courses in key areas for career management and growth, including Time Management, Digital Skills, Creativity and Soft Skills.

Course Notes

Important Lab Environment Information: This is a LECTURE ONLY eLearning course. If you wish to practice with hands-on activities, you will need to have access to the software required for this course.

Prerequisites

Knowledge Prerequisites:

Basic familiarity with the Python programming language (variables, loops, functions).
A general understanding of data and basic analytical concepts.

Suggested Course Prerequisites:

eLearning

Introduction to Python

7 Courses

Bundle Objectives

Master the basic and advanced functionalities of Jupyter Notebooks for interactive data work.
Set up a working environment using the essential Python Libraries within the Anaconda distribution.
Apply Exploratory Data Analysis (EDA) techniques to identify key trends and areas of investigation in datasets.
Prepare data effectively for predictive modeling and machine learning applications.
Plan and train various machine learning classification models.
Implement K-Fold Cross-Validation to rigorously evaluate model performance.
Use validation curves and dimensionality reduction to optimize and enhance model accuracy.
Develop the skill to scrape tabular data from web pages for custom data acquisition.
Transform scraped data efficiently into Pandas DataFrames for manipulation and analysis.
Create and deploy interactive, web-friendly visualizations to present findings clearly.
Work through a complete data analytics report example to understand the full data science pipeline.

Target Audience

This course is suitable for:

Beginner Data Analysts: Individuals with some Python background looking for a quick entry point into the data science workflow and libraries.
Students and Academics: Learners who need practical, hands-on experience with Python and Jupyter for data-driven projects and research.
Aspiring Data Scientists: Professionals seeking foundational training in core machine learning, data cleaning, and visualization concepts.
Software Developers: Developers who want to transition their existing Python programming skills into the data and analytics domain.

Key Features

Audio Narration
Video

Languages

Audio/Video/Course Text: American English.
Subtitles (Closed Caption): N/A.

Course Duration

Packages for Problem Solving: 2 hr 49 min

Essential Career Skills Pack: 2 hr 23 min

eLearning Training Delivery Method

Learn at Your Own Pace

This self-paced online course lets you learn independently at your own pace through Certstaffix Training's easy-to-use platform.

How It Works

A Learn at your own pace - Start and stop as it is convenient for you. Pick up where you left off.

Lecture utilizing video and recorded screenshots

6-month subscription length

Instant Access After Purchase

Have more than 10 students needing this course? Contact Us for bulk pricing.

Course Topics

Beginning Data Science with Python and Jupyter

Course Duration - 2 hr 49 min

Getting started with data science doesn’t have to be an uphill battle. This step-by-step video course is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You will learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world.

We'll start with understanding the basics of Jupyter and its standard features. You will be analyzing an example of a data analytics report. After analyzing a data analytics report, next step is to implement multiple classification algorithms. We’ll then show you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Finish up by learning to visualize this data interactively.

Course Objectives:

Identify potential areas of investigation and perform exploratory data analysis
Plan a machine learning classification strategy and train classification models
Use validation curves and dimensionality reduction to tune and enhance your models
Scrape tabular data from web pages and transform it into Pandas DataFrames
Create interactive, web-friendly visualizations to clearly communicate your findings

Detailed Course Outline:

Lesson 1: Jupyter Fundamentals

Basic Functionality
Useful Features of Jupyter
Python Libraries
Our First Analysis - The Boston Housing Dataset
Introduction to Predictive Analytics
Lesson Summary
Assessments

Lesson 2: Data Cleaning and Advanced Machine Learning

Preparing to Train a Predictive Model–Part 1
Preparing to Train a Predictive Model–Part 2
Training Classification Models
K-Fold Cross-Validation
Lesson Summary
Assessments

Lesson 3: Web Scraping and Interactive Visualizations

Scraping Web Page Data
Interactive Visualizations
Lesson Summary
Assessment

Essential Career Skills Pack

Productivity and Time Management

Course Duration - 30 min

It seems that there is never enough time in the day. But, since we all get the same 24 hours, why is it that some people achieve so much more with their time than others? This course will explain how to plan and prioritize tasks, so that we can make the most of the limited time we have. By using the time-management techniques in this course, you can improve your ability to function more effectively – even when time is tight and pressures are high. So, by the end of the course you will have the knowledge, skills and confidence to be an effective manager of your time.

Course Objectives:

Set your priorities to better manage your time
Improve your productivity by sharpening your focus and multitasking effectively

Detailed Course Outline:

Productiity & Time Management
Prioritization
Getting Things Done

Procrastination
Multitasking & Focus
Summary

Basic Digital Skills

Course Duration - 13 min

With the rise of digital transformation and technology, having a basic digital literacy is essential for all types of jobs, regardless of the industry. To stay competitive and be successful in the workplace, enhancing your digital skills should be a top priority.

Course Objectives:

Recall the essential digital skills framework
Elaborate on the toolkit of essential digital skills
Identify how to develop or improve your digital skills

Detailed Course Outline:

The Essential Digital Skills Framework
The Toolkit of Essential Digital Skills

Developing Digital Skills
Summary

4 Ways to Boost Creativity

Course Duration - 30 min

The digital economy is opening up ways for everyone to be creative. It doesn’t just mean being artistic – it’s more about ideas, solutions, alternatives, incremental improvements. Peter Quarry and Eve Ash discuss ways that mental capacity can be developed, perspectives changed, group power leveraged and making things actually happen.

Course Objectives:

Define creativity
Think outside the box
Develop the right mental attitude
Leverage the power of groups
Ensure managers make it happen

Detailed Course Outline:

What is Creativity at Work?
Learn to Think Outside the box
Develop the Right Mental Capacity

Laverage the Power of Groups
Ensure Managers Make It Happen
Summary

The 11 Essential Career Soft Skills

Course Duration - 1 hr 10 min

Soft Skills are the traits, characteristics, habits, and skills needed to survive and thrive in the modern work world. Soft skills aren't usually taught in school, but you will learn them all here in this course. Are you someone that other people in your organization and industry like to work with, collaborate with and partner with? Are you seen as a valuable asset to any new project that comes along?

This soft skills training course will teach you how to develop the skills that can make the difference between a lackluster career that tops out at middle management versus one that lands you in the executive suite. Or to wherever you define career success. So many soft skills seem like common sense at first glance, but they are not commonly applied by most workers. This soft skills training course will give you an edge over your competitors. It will also make your job, your career and your life more rewarding and enjoyable.

Course Objectives:

Understand how to be a great communicator
Become a stronger listene
Appear professional to co-workers and bosses of all ages
Avoid common career blunders that often end careers
Manage expectations for bosses and colleagues
Position yourself for promotions
Make technology your asset, even if you are afraid of technology
Avoid the Not My Job Syndrome
Develop EQ to Match Your IQ
Develop leadership qualities

Detailed Course Outline:

Introduction
The Soft Tech Savvy Way to Always Be Essential
Not My Job, And I Am Happy to Do It
You Can Become a Master Communicator
Feedback Video for The 11 Essential Career Soft Skills
Become a Leader Without the Title or Formal Authority

Your EQ Will Beat a Higher IQ
Building Your Winning Team
Make Every One of Your Seconds Count
Unleash Your Inner Anthony Robbins
Avoid Being Uncool
Clothes Can Still Make or Break Your Career
Conclusion The 11 Essential Career Soft Skills
Extra: Developing Your Career Secret Sauce

Related Data Science Information:

How Much Do Data Science Training Courses Cost?

Public instructor-led Data Science course prices start at $275 per student. Group training discounts are available.

Self-Paced Data Science eLearning courses cost $300 at the starting point per student. Group purchase discounts are available.

Which courses are best for data science?

A: There is no simple answer to the question of which courses are best for data science. The field of data science is vast and complex, and there are many different specialties within it. That said, there are some general principles that can guide students in choosing the right courses for their needs.

First, students should make sure that they have a strong foundation in mathematics and statistics. These subjects are the backbone of data science, and without a strong understanding of them, it will be difficult to excel in the field.

Second, students should choose courses that cover a broad range of topics. Data science is a multidisciplinary field, so it is important to have knowledge in multiple areas. This will give students a well-rounded education and prepare them for the diverse challenges they may face in their career.

Third, students should consider taking courses that focus on specific domains or applications of data science. While a broad education is important, it is also helpful to have expertise in specific areas. This can be especially useful for students who want to pursue a specific career path or specialize in a certain type of data analysis.

Finally, students should make sure to choose courses that are taught by experienced and knowledgeable instructors. Data science is a rapidly changing field, and it is important to learn from those who are at the forefront of its development. By taking courses from leading experts, students can be sure that they are getting the most up-to-date and accurate information.

Choosing the right courses for data science can be a challenge, but by following these guidelines, students can ensure that they are getting the best possible education. With a strong foundation in mathematics and statistics, and a broad understanding of the field, students will be well-prepared to pursue a successful career in data science.

How do I train to be a data scientist?

A: There is no one-size-fits-all answer to this question, as the best way to train to be a data scientist will vary depending on your previous experience and skills. However, there are some general tips that can help you get started:

1. Firstly, it is important to have a strong foundation in mathematics and statistics. This will give you the ability to understand and work with complex data sets.

2. Secondly, it is also beneficial to have experience in programming languages such as R or Python. These languages are commonly used by data scientists and will be essential for working with data.

3. Finally, it is also helpful to have some experience in machine learning. This will allow you to build models that can automatically learn and improve from data.

These are just some general tips to get you started on the path to becoming a data scientist. For more specific advice, it is best to consult with someone who is already working in the field.

Does data science require coding?

A: No, data science does not require coding. However, coding can be a helpful tool for data scientists who want to manipulate and analyze data. There are many different ways to analyze data, and coding can give you more control over the process. It can also help you automate repetitive tasks. Ultimately, whether or not you code is up to you and what works best for you and your team.

Some data scientists do not code at all, while others are proficient in multiple programming languages, such as R and Python. There is no one right way to do data science, and the tools you use will depend on your individual skills and preferences. If you're new to data science, it may be helpful to learn some basic coding skills. This will give you a better understanding of how data science works and how to manipulate data. However, you don't need to be a coding expert to be a successful data scientist. Ultimately, the most important skill for data scientists is the ability to think critically and solve problems. If you're good at that, you can learn whatever coding skills you need along the way.

What are the top Data Science skills?

A: There is no doubt that data science is one of the hottest fields in the tech industry right now. And with good reason – businesses of all sizes are looking to harness the power of data to gain insights that can help them improve their operations and bottom line.

But what does it take to be a successful data scientist? In addition to strong technical skills, data scientists must also be able to effectively communicate their findings to non-technical stakeholders and have a keen business sense to know how their insights can be applied to real-world problems.

Top Data Science Skills

Technical Skills

First and foremost, data scientists need to have strong technical skills. This includes a deep understanding of statistics and machine learning algorithms, as well as experience working with large datasets. Additionally, data scientists should be proficient in at least one programming language, such as Python or R, and have experience using data visualization tools like Tableau or D3.js.

Communication Skills

Data scientists must be able to effectively communicate their findings to non-technical stakeholders. This includes being able to explain complex statistical concepts in layman’s terms and creating clear and concise data visualizations that tell a story. Additionally, data scientists should be able to make recommendations on how their insights can be applied to solve real-world business problems.

Business Skills

Finally, data scientists need to have a keen business sense to know how their insights can be applied to real-world problems. This includes understanding the business goals of their organization and being able to translate their findings into actionable steps that can help achieve those goals. Additionally, data scientists should be familiar with common business metrics and KPIs, as well as how to use data to measure and improve those metrics.

While there is no one-size-fits-all answer to the question of what skills data scientists need to succeed, the above three skills are a good foundation on which to build. As data science continues to evolve, data scientists will need to continuously adapt their skillset to keep up with the latest trends and technologies.

Where Can I Learn More About Data Science?

Data Science Blogs

Data Science User Groups

Data Science groups | Meetup

Data Science Online Forums

Explore Data Science Training Classes Near Me:

Certstaffix Training provides Data Science classes near me or online, depending on the number of students involved. We offer online courses for individual learners, as well as in person classes at your office for corporate groups. Our trainers are highly experienced professionals with the expertise necessary to help you gain a thorough understanding of Data Science concepts and tools. With our courses available online for individuals or in person for corporate groups, it's easy to develop your Data Science skills. Start learning today and see how Certstaffix Training can help you reach your goals.

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