Data Analyst Course in London, UK

IBM is a leading cloud platform and cognitive solutions company. Since its founding in 1911, IBM has become one of the largest global technology and consulting employers, with 350,000+ employees working in 170 countries. It has collaborated with Simplilearn to give students a once-in-a-lifetime kind of exposure helping them outstand themselves in Artificial Intelligence and Data Science. Simplilearn’s Data Analyst course in London is one of the most popular courses for students as it offers excellent data analysis skills.

After partnering with Watson, IBM is working on an AI platform for business, powered by data and trying to build industry-based solutions for real-world problems. For 70 years, IBM continues to create future of Information Technology with more than 3000 researchers driving innovation in 12 labs located across six continents.

What can I expect from this Simplilearn's Data Analyst program developed in collaboration with IBM?

Once you complete your Data Analyst course in London, you’ll be given a course completion certificate from IBM and Simplilearn. This certificate is proof that you have finished your data analyst training in this Data Analyst Training in London, giving you an edge in the job market. You will also have these things with you if you complete the course –

1. Access to IBM cloud platforms that feature IBM Watson and other software.
2. Industry-recognized Data Analysis Master’s certificate from Simplilearn.
3. USD 1200 worth of IBM cloud credits that you can use for hands-on exposure.

The Data Analyst Course in London, which is known to have been developed in collaboration with IBM, aims to provide people with immense expertise in booming data analytics. Our training course helps in imparting ways to master inferential and descriptive statistics, data blending, hypothesis testing, regression analysis, forecasting, and data extracts. With such a course, one can also gain data visualization expertise techniques using Power BI and Tableau coupled with learning how data can be organized, and dashboards can be designed. With the help of such a course, people with a simple understanding of mathematical concepts can also complete the course and become data analytics experts.

Such a learning experience helps to blend the knowledge of Data Analytics with demos and projects through CloudLab. With the successful completion of the course in London, one will possess all the required skills to become a Data Analyst successfully.

The learning path in our Data Analyst course in London is structured to give learners the tools they need to be successful in Data Analysis. It also helps in providing a competitive edge, and therefore, by the end of the Data Analyst Certification in London, one will be able to: 

• Comprehend important statistical topics such as measures of central tendency, regression, correlation, and dispersion
• Master SQL command, Universal Query Tool, and other such SQL concepts
• Write one's first Python program with the implementation of concepts of conditions, functions, variables, loops, and strings 
• Comprehend the implications of sets, conditions, dictionaries, lists, branching, classes, and objects in Python 
• Work with data via Python, and this includes writing and reading of files, working, loading, and saving up data with the help of Pandas
• Acquire knowledge about the interpretation of data in Python by the use of NumPy's multidimensional arrays, Pandas' DataFrames, the library of mathematical routines by SciPy, and the execution of machine learning with the help of Scikit-Learn 
• Using popular Python libraries to perform data analytics
• Gaining insights on various libraries for data visualization in Python such as Folium, Matplotlib, and Seaborn 
• Gaining a deep understanding of the basics of R and learning to write one's R scripts 
• Understand the execution of various statements in R while mastering R programming in the process 
• Using and understanding linear and non-linear models of regression and techniques of classification for data analysis 
• Using and learning K-means, hierarchical clustering, DBSCAN, and other such clustering methods 
• Gaining an elementary knowledge of the business analytics that are using Excel 
• Gaining cognizance about the latest visualization tools and Microsoft analytics 
• Becoming proficient with Tableau statistics by grasping the concepts of Tableau Desktop 10 and, after that, building enticing dashboards
• Becoming an expert on techniques for visualization like treemap, heat map, Gantt chart, Pareto, market basket analysis, and waterfall

Our Data Analyst course in London gives student the opportunity to work on over 15 industry-based and real-life projects to help students master the concepts of business intelligence and analytics such as data blending, data visualization, decision trees, and much more. Various projects are mentioned hereafter:

Project 1: Examining how big companies such as Flipkart and Amazon make the use of tools of business intelligence for performing category analysis
Project Title: Category Performance Analysis
Description: According to the Performance Evaluation Program, the subcategories that yield a consistent profit for the previous four years are awarded as the Best Performing Subcategories. One can help the manager pinpoint the top subcategories based on profits earned and utilize the advanced features in the dashboard to show a full picture of the subcategory sales.
 
Project 2: Learning how BSE, NSE, NASDAQ, and other such stock markets leverage data analytics and science for arriving at consumable data from complicated datasets
Domain: Stock Market
Description: Being part of a Data Analyst course in London, one will import data using Yahoo data reader for many companies such as Yahoo, Google, Apple, Microsoft, and Amazon. One can also conduct fundamental analytics, which incorporates the plotting closing price, plotting stock trade by volume, performing daily return analysis, and revealing the relationship between various stocks using a pair plot.

Project 3: Watch how various banks like Bank of America, HDFC, Citigroup, and ICICI make use of data analysis for staying ahead of the competition
Domain: Banking
Description: To convince potential customers to invest in a bank term deposit, a Portuguese banking institution once ran marketing campaigns which were conducted via phone calls. There were times when the very same customer ended up being contacted a few times. Your job is to analyze all the data collected from such a marketing campaign.

Project 4: Learn how leaders of many famous healthcare industries use data analysis for leveraging business 
Domain: Healthcare
Description: For mediating hospital readmissions, Predictive Analytics can effectively be used. Predictors are very useful in healthcare and other industries when they can be shifted into action, but without intervention, real-time and historical data are worthless. For judging the value and efficiency of a forecasted trend and dynamic behavior, both the invention and the predictor must be integrated into a similar system and workflow at the place where the trend happened originally. 

Project 5: Understanding how Amazon, Walmart, Target, and other leading retail companies use data analysis for optimizing and analyzing their inventory and product placements
Domain: Retail
Description: Analytics is used for the optimization of product placements on shelves or inventory in warehouses using industry examples. With this project, participants can learn the cycle of product optimization from warehouses to shelves. This helps retail sectors to provide insights into regular occurrences.

Project 6: Understanding how AIG, Berkshire Hathaway, AXA, and other insurance leaders use data analysis by working on insurance-based real-life projects
Domain: Insurance
Description: According to the Insurance Predictive Modeling Survey conducted in 2013, the use of predictive analytics in the Data Analyst course in London has significantly increased in big companies. Though the survey depicted an increase in predictive modelling all through the industry, respondents from many companies that are known to write personal insurance of over $1 billion employ it, as and when compared to 69% of the companies with a comparatively lesser premium.

Professionals of any educational background who are aspiring and possess an analytical frame of mind are best for pursuing a Data Analyst course in London; this includes:

• IT professionals
• Marketing managers
• Supply chain network managers
• Students in PG or UG programs
• Sales professionals
• Beginners in the data analytics domain
• Banking and finance professionals

Learners who desire to prevail in our Data Analyst course in London and certification training should hold basic skills in mathematics.

By finishing our Data Analyst course in London, the student will get the essential data analysis skill set to work as an accomplished Data Analyst. Various job titles are:

• Analytics Manager or lead
• Data Analyst
• Business Intelligence Analyst
• Business Intelligence Engineer 
• Business Analyst/Senior Business Analyst
• Various managerial roles

As predicted by the World Economic Forum, 2022 will witness Data Analysts as one of the top emerging jobs in society. Data analysis is viewed by organizations today as one of the most important specialties for the future due to the value the data is capable of delivering. Considering a Data Analyst course in London, data in the business environment in this day and age is much more accessible and abundant than ever. Each day, about 2.5 quintillion bytes of data are created. Data analyzers' value will continue to grow while creating new jobs and advancement opportunities for a career with an increasing skill gap in data analytics.

Professionals who enter the field of Data Analytics are known to reap the benefits of picking up a job and enjoying fruitful salaries. According to a recent IBM report, jobs you can get by taking a Data Analyst course in London are anticipated to increase by 15% to 2.72 million in 2021, with the most notable demand for IT, Financial, and Insurance Analysts. According to Glassdoor, in 2019, Data Analysts earn about $67,366 as an average pay.