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Course / Course Details

Data Science and Analytics

  • Joy Jesubi image

    By - Joy Jesubi

  • 18 students
  • N/A
  • (0)

Course Requirements

  • Anyone can learn and become a data analytics professional. However, here are some prerequisites that would be helpful for choosing a career in data analytics: Ability to work with numbers and quantitative stuff
    Some programming experience
    Willingness to learn statistical concepts
    Passion for solving problems
    If you plan to switch to being a data analyst but bear no experience in the industry, this data analytics tutorial will provide you with a strong foundation in the subject.

Course Description

Data is every detail of our very existence. Consciously or not, we all contribute to global data and this data is relevant to different organizations, in different forms to aid important decision-making processes. Data analytics is the science of analyzing data and extracting meaningful information that can be used to make better decisions in an organization. This is something we all start doing from an early age. Analytics will help demystify data, so you can use it to make informed decisions, recognize trends, detect outliers, and summarize data sets to inform business decisions.

Everything we do involves systems and processes. We buy and sell things; we eat, we travel, we watch TV, we surf the internet, we listen to music. With all this activity taking place, global businesses are drowning in data, and they increasingly rely on people with good analytics skills to inform organizational decision-making. Overtime, the importance of data analytics have risen and this has led to the demand for analytical skills.

It’s the data analyst’s job to translate the data into actionable — and profitable — business intelligence.

In this course, you will learn:

  • introduction to data
  • Data science pathway
  • Data sourcing
  • Data analytics
  • Data ecosystem
  • Data wrangling
  • Data mining

    Go above and beyond your peers by gaining the skill packed in this course.

Course Outcomes

In this course you will learn: what data science and analytics is all about, how to scrap data, data mining, how to import and export data, data visualization

Course Curriculum

  • 10 chapters
  • 41 lectures
  • 8 quizzes
  • N/A total length
Toggle all chapters
1 what is Data
N/A

2 MODULE 1.1-1.5
N/A

3 MODULE 1.6-1.7
N/A

4 Data science Explianed
N/A

5 Data Science Quiz [Quiz]
Start
10 Min

1 MODULE 2
N/A

2 Methods Overview
N/A

3 What is BI
N/A

4 Big Data
N/A

5 LAB 1 - BIG DATA
N/A

6 Quiz 2 [Quiz]
Start
10 Min

1 MODULE 3
N/A

2 Data Sourcing Explained
N/A

3 LAB 2
N/A

4 Quiz 3 [Quiz]
Start
10 Min

1 MODULE 4
N/A

2 Data Science vs Data Analytics
N/A

3 Data Analytics Explained
N/A

4 LAB 3
N/A

5 DATA ANALYTICS QUIZ 4 [Quiz]
Start
10 Min

1 Python fundamentals
N/A

2 Navigating Anaconda
N/A

3 Practicals
33 Min

1 MODULE 5
N/A

2 Data Ecosystem Explained
N/A

3 LAB 4
N/A

4 Data science quiz 5 [Quiz]
Start
10 Min

1 Web and Social media
6 Min

2 Web and Social media Monitoring
3 Min

3 LAB 5
N/A

1 MODULE 6
N/A

2 Data Wrangling Explained
N/A

3 Data science and analytics quiz 6 [Quiz]
Start
10 Min

4 LAB 6
N/A

1 MODULE 7
N/A

2 Data visualization with Tableau
2 Min

3 Data Mining Explained
N/A

4 LAB 7
N/A

5 Data science and Analytics quiz 7 [Quiz]
Start
10 Min

1 Course Reference
N/A

2 FINAL EXM [Quiz]
Start
20 Min

1. LAB 1: CREATING YOUR OWN DATA SCIENCE LAB MODULE 1
2. LAB 2: CREATING A DATAFRAME WITH PANDAS MODULE 2
3. LAB 3: SCRAPING INSTAGRAM WITH PYTHON MODULE 3
4. LAB 4: ANALYZING MUSIC TRENDS ON YOUTUBE WITH PYTHON MODULE 4
5. LAB 5: CREATING AN XML FILE MODULE 5
6. LAB 7: INSTALLING TABLEAU PUBLIC MODULE 7

Instructor

Joy Jesubi

5 Rating
2 Reviews
205 Students
5 Courses

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  • Duration N/A

  • Lectures 41 lessons

  • Enrolled 18 students

  • Category: Data Analysis

  • 8 Quizzes

  • Language: English

  • Skill Level Beginner

  • Certificate of Completion

  • Full lifetime access

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